Autophagy: Cancer, Other Pathologies, Inflammation

AUTOPHAGY

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AUTOPHAGY CANCER, OTHER PATHOLOGIES, INFLAMMATION, IMMUNITY, INFECTION, AND AGING VOLUME 11 Edited by

M. A. Hayat

Distinguished Professor Kean University Union, New Jersey

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1800, San Diego, CA 92101-4495, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2017 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-805420-8 For Information on all Academic Press publications visit our website at https://www.elsevier.com

Publisher: Sara Tenney Acquisition Editor: Linda Versteeg-buschman Editorial Project Manager: Halima Williams Production Project Manager: Julia Haynes Designer: Greg Harris Typeset by MPS Limited, Chennai, India

Dedication To: Julio A. Aguirre-Ghiso, Patrice Codogno, Eduardo Couve, Ana M. Cuervo, Guido R.Y. De Meyer, Vojo Deretic, Fred J. Dice, William A. Dunn Jr., Nicolas Dupont, Eeva-Lisa Eskelinen, Sharon Gorski, Roberta A. Gottlieb, Tanya M. Harding, Xuejun Jiang, Tomotake Kanki, Vladimir Kirkin, Daniel J. Klionsky, Massaki Komatsu, Guido Kroemer, Beth Levine, Noboru Mizushima, Nobuo N. Noda, Yoshinori Ohsumi, Brinda Ravikumar, Fulvio Reggiori, David Rubinsztein, Isei Tanida, Michael Thumm, Sharon A. Tooze, Miki Tsukada, Herbert W. Virgin, Eileen White, Tamotsu Yoshimori, and others. The men and women involved in the odyssey of deciphering the molecular mechanisms underlying the complexity of the autophagy process that governs our lives.


Dedication In gratitude to: Philip Connelly and Kimberly Fraone for their generosity and help


Knowing Autophagy There is debate and stress About what is the best Autophagy test. You can delve inside This or Klionsky’s Guide To help you decide. This volume is thick But the reading is quick So you’ll know every trick. Cells that are stressed Will do their best To clean up the mess. Many cell types agree That the best strategy Is macroautophagy. It doesn’t always suffice And in cancer-prone mice One had better think twice. Before you’re aware Of a need for DNA repair Praise be, autophagy’s there. Roberta A. Gottlieb


10 Lines of Autophagy for Volume 10 Autophagy is needed before you’re born To ensure successful embrogenesis And at every turn along the way Autophagy’s there to prevent apoptosis. A two-edged sword is autophagy’s role In cancer survival and chemoresistance Yet tumor suppression also depends upon Autophagy’s help to lower cell malignance. Clear thinking is needed to know when and how To invoke autophagy for lifelong gain Autophagy prevents mental deterioration, By slowing degeneration in the aging brain. Eating too much is a global problem Autophagy’s suppressed and we store debris Autophagy helps to clear the fat From brain and heart and coronary artery. So let us fast and pay homage To a transient organelle, the autophagosome Whose greatness is revealed in chapter and verse Of Volume 10, this noble tome! Roberta A. Gottlieb


Mitophagy and Biogenesis mTOR and nutrient sensors control Autophagy processes in all of our cells Dozens of proteins must play each their role To enable engulfment of bad organelles. Those who are young may mistakenly think one Is safe and immune to the dangers of aging But if you are lacking in proper PINK1 Mitochondrial fires are already raging. For insight and knowledge some turn to the fly; Drosophila’s genes can help us discover The causes of aggregates seen in the eye, And even find drugs to help us recover. Ubiquitin’s role in degeneration Is to set out red flags on relevant cargo Marking the junk that needs degradation At a pace that is presto rather than largo. Mitochondria fear Parkin known as PARK2 Whose ubiquitin tags on two mitofusins Determine the fate of one or a slew, For a lonely short life of network exclusion. Their fate is ensured by sequestosome 1 Who recruits membranes rich with LC3-II Autophagosome to lysosome a perfect home run Cellular housekeeping momentarily through. But the work isn’t over and the job isn’t done Unless Paris is tagged with ubiquitin too Then repression is lifted form PGC1 So biogenesis starts and mitos renew! Roberta A. Gottlieb


Life in the Balance, Longevity the Goal Self-eating, recycling, cash-for-your clunkers: Trade up to the mitochondrial equivalent Prius. The road to rejuvenation is paved with destruction For clearing the rubble precedes reconstruction But remember that life’s circular dance Depends on opposite forces in balance Excess destruction, too much biogenesis, Brings heart failure, cancer or neurodegeneries Roberta A. Gottlieb


Autophagy and Cancer When speaking of cancer, autophagy’s good By culling mitochondria and clearing deadwood Autophagy limits the radical chain That breaks DNA and mutates a gene That makes a cell double, so careless and mean In order for cells to malignant transform They lose mitochondria except for a few Using glycolysis as the source of their fuel How they achieve mitochondrial decimation Is nothing more than autophagic elimination. Then one cell is many, an ominous mass Demanding more glucose, hungry and crass, Directing formation of artery and vein Til capsular fibers give way under strain Then cancer cells spread so far and so wide They demand blood vessels the body provide But until those are patent the tumor cells strive To rely on autophagy to neatly survive The hurdles required for metastasis Until blood flow’s established for cancerous bliss. Blocking autophagy sends them over the brink And how chloroquine works, we think But tumors are slowed by statin’s effects Which induce autophagy and tumor cell death Autophagy’s good, autophagy’s bad The confusion’s enough to drive us all mad So study we must, and learn ever more Til enlightenment finally opens the door Oncologists must heed the tumor’s agenda And decide whether autophagy is a foe or a friend? Roberta A. Gottlieb


Some Thoughts on Autophagy and Immunity A bacterium squirmed into a cell Thinking “This home will serve me well” The cell objected quite forcefully Encasing the bug in LC3 Saying “I’m not your home, You’re imprisoned in my autophagosome!” The bug merely shrugged and secreted a factor Poking holes in the shell, releasing the actor Who by now had multiplied so many times They were all ready to commit more devious crimes. Autophagy’s a way to lock those critters away But bugs evolve too, and have learned what to do To turn host defense to their convenience. So mark my words and mark them well If you want to be a clever cell Turn autophagy up to kill pathogen C, D, or E But keep it turned down for bugs A, B, and D. How to do that? Eating no meat and eating no fat Will turn up the autophagy thermostat. But sugar and fat and protein too Will slow it down as good as glue. Remember a rich diet keeps autophagy quiet Skip brunch and sup to turn autophagy up. Trouble comes as the number one, If it’s interleukin-1…Beta, that is. Relief comes as the number three LC3…B, that is. Letters and numbers, numbers and letters Stop getting dumber and learn from your betters. Autophagy works to prevent calamity By turning down inflammity.

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Some Thoughts on Autophagy and Immunity

Autophagy’s a way to share information From macrophages by antigen presentation To lymphocytes of each denomination When properly goaded, MHC-IIs are loaded With tasty bites of foreign peptides. Endosome to lysosome Bits of the stranger are made known To help program immunity, Thanks be to you, autophagy! Roberta A. Gottlieb

Autophagy: Friend or Foe? Be careful when hugging Atg5 It can help you get dead or be live. When Atg12’s covalently bound Autophagy’s up and death can’t be found. But if protease scissors free the BH3 Fragment of Atg5, soon you will see Death and destruction, known as Programmed cell death or apoptosis. Beclin 1 is capricious too, Hitching itself to Bcl-2. In this way it deflects Bcl-2’s survival effects. But helped by VPS34 It forms a phagophore: Autophagy goes well And rescues the cell. Roberta A. Gottlieb


Autophagy: If and When Like a foreign body embedded in scar Membrane shrouds the mitochondrion Lest it activate the inflammasome And trigger release of IL-1. Of course we need an antidote To avoid the damage from mitos gone bad Enter the savior—mitophagy, Rescuing the cell like Sir Galahad. Another case where autophagy’s good Is in the aging, sludgy brain Where it serves to clear proteinaceous crud: Autophagy to the rescue, once again. The bleakest core of a malignant mass Like a hypoxic inner circle of Hell Is where autophagy plays a darker role To aid in the survival of cancer cells. Do we want to trigger autophagy? We need to know how, where, and when. Read this book of cellular wizardry And then you’ll know: It all depends! Roberta A. Gottlieb


What Happened When Autophagy Didn’t A mito decayed and leaked DNA Plus cytochrome c and 8-oxo-dG The inflammasome blew And the apoptosome too And the cell had a very bad day. Roberta A. Gottlieb


Sugar Isn’t Always Sweet When your heart is worn and skips a beat Membranes keep it in or out And insulin gives a special route Glut transporters form a pore Bringing sugar in the open door Too much is bad-too little, too: Cells need the proper fuel. Inside the cell sugar’s stored Glycogen the sweetest hoard. Two enzymes live to break it down: A neutral enzyme can be found In cytosol where granules roam, But in the acidic lysosome Another waits on bended knee To play its role in glycophagy. Excess carbs are bad: this much is clear. So consider maltose when quaffing beer! Roberta A. Gottlieb


Mitochondrial Mysteries We know so much yet understand so little About mitochondrial ox-phos and fusion and fission, Mitochondrial autophagy and biogenesis. MitoTimer and lenses have given us celluvision. Though heart cells live years it’s quite different within: Mitochondrial life is counted in weeks. Outer and inner membrane proteins vary yet more In their lifespans revealed by mass spectrum peaks. Protein import must match what’s inside, Lest proteins unfold and fall prey to Lon. The peptides escape to the cytosol To trigger transcription of chaperones. Try we must to describe and define The complex nature of the proteome, As mitochondria expand and divide, Fragment and fall into autophagosomes. Yet for all we know and all we learn The mysteries grow and questions expand Like Mandelbrot sets of fractal images, We see the work of divinity’s hand. Roberta A. Gottlieb


A Photo Is Static, An Instant in Time Telling nothing that happened next or before; Yet papers are published and conclusions are drawn Claiming autophagy’s up when really it’s gone. Like tea leaves or runes it’s not easy to read When puzzling out blots of LC3B When chloroquine’s there or when it’s left out It’s the increase that matters to tell you what’s what. Beclin is tricky when it’s gone half away, Its effects on autophagy go every which way: Nucleation is up or fusion’s not seen, So consider with care what it all means. Like freeways with cars and crowded on-ramps AVs have cargo and their own traffic jams Created by leupeptin, CQ or Baf, LC3 rises at least by a half. Remember when calculating if flux is intact It’s the ratio that gives you that crucial fact LC3 levels of Baf over static Will yield results that are not so erratic. To understand the process you must think it through; Autophagy requires you to use every clue. Good data help you line up ducks, Just please be sure to measure flux. Roberta A. Gottlieb


Autophagy Subversion A bug grew tired of living alone, Entered a cell and called it home. The cell disagreed, Wrapped it in LC3, And shipped it off to the lysosome. Clever bacteria know such is the plan And evolve new ways to beat the man. Roberta A. Gottlieb


Contents Foreword by Roberta A. Gottlieb xxxix Foreword by Eeva-Liisa Eskelinen xli Preface xliii Contributors xlvii Autophagy: Volume 1—Contributions lxi Autophagy: Volume 2—Contributions lxiii Autophagy: Volume 3—Contributions lxv Autophagy: Volume 4—Contributions lxvii Autophagy: Volume 5—Contributions lxix Autophagy: Volume 6—Contributions lxxi Autophagy: Volume 7—Contributions lxxiii Autophagy: Volume 8—Contributions lxxv Autophagy: Volume 9—Contributions lxxvii Autophagy: Volume 10—Contributions lxxix

I MOLECULAR MECHANISMS 1. Overview of Autophagy M.A. HAYAT

Specific Functions of Autophagy (A Summary) 9 Autophagy Process 10 Autophagy in Normal Mammalian Cells 10 Endoplasmic Reticulum 11 Major Types of Autophagies 13 Autophagosome Formation 15 Autophagic Flux 16 Autophagic Lysosome Reformation 17 Autophagy as a Double-Edged Sword 18 Protein Synthesis 19 Autophagic Proteins 28 Aggrephagy 31

Monitoring Autophagy 33 Reactive Oxygen Species 33 Mammalian Target of Rapamycin 34 Role of Autophagy in Tumorigenesis and Cancer 35 Autophagy and Immune System 37 Autophagy and Senescence 39 Role of Autophagy and Cellular Senescence in Aging 39 Role of Autophagy in Viral Defense and Replication 46 Role of Autophagy in Intracellular Bacterial Infection 47 Role of Autophagy in Heart Disease 48 Role of Autophagy in Neurodegenerative Diseases 49 Cross Talk Between Autophagy and Apoptosis 51 Autophagy and Ubiquitination 55 Autophagy and Necroptosis 55 Mitochondrial Fusion and Fission 56 Selective Autophagy 56 References 75

2. Methods for Measuring Autophagosome Flux—Impact and Relevance ANDRE DU TOIT, JAN-HENDRIK S. HOFMEYR AND BEN LOOS

Introduction 92 Measuring Autophagic Flux—A Slope Rather Than a Column 93 Quantifying the Autophagic Flux Deviation With Precision 96 Modeling the Autophagy System—Key Determinants Characterized by Rates 98 Summary, Conclusion, and Future Outlook 101 Acknowledgments 102 References 102

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3. Loss of Pigment Epithelial Cells Is Prevented by Autophagy YOON H. KWON, YEON A. KIM AND YOUNG H. YOO

Introduction 106 Anatomy and Histology 106 Function of the RPE 108 Exposure to Potential Damage 110 Autophagy in the RPEs 111 αB-Crystallin and Autophagy 114 Conclusions 115 Acknowledgment 115 References 115

4. Role of Autophagy Inhibition in Regulating Hepatic Lipid Metabolism: Molecular Cross Talk Between Proteasome Activator REGγ and SirT1 Signaling XIAOTAO LI AND LEI LI

Introduction 120 Proteasome Links Autophage and Lipid Metabolism– Molecular Mechanisms 123 Molecular Switch: REGγ-Sirt1 Cross Talk Modulates Autophage Activity in Lipid Metabolism 126 Discussion 129 Acknowledgments 130 References 130

5. Role of Autophagy in Regulating Cyclin A2 Degradation: Live-Cell Imaging ABDELHALIM LOUKIL AND MARION PETER

Introduction 133 Autophagy Regulates Protein Turnover 134 Mitotic Autophagy, a Failsafe Mechanism 135 Monitoring a Nonclassical Substrate of Autophagy, Cyclin A2 136 Discussion 139 References 139

7. The Role of Histone Deacetylase Inhibition in the Accumulation and Stability of Disease-Related Proteins ELIZABETH A. THOMAS

Introduction 160 Histones and HDAC Enzymes 160 HDAC Inhibitors 163 Ubiquitin Proteasomal and Autophagy Pathways 166 Protein Folding Disorders/Proteopathies 167 A Role for HDAC Inhibitors in Proteopathies 169 Conclusions/Future Perspectives 176 References 176

8. The Role of Atg9 in Yeast Autophagy HENNING ARLT AND FULVIO REGGIORI

Introduction 182 Structure and Role of Atg9 in Autophagy 183 Atg9 Trafficking via ER and Golgi Compartments 184 Atg9 Vesicles/Reservoirs Contribute to the Formation of the Preautophagosomal Structure 186 Atg9 Roles at the Preautophagosomal Structure 187 Atg9 Recycling From Autophagosomal Membranes 188 Concluding Remarks 189 Acknowledgments 190 References 190

II ROLE IN DISEASE

6. Roles of Rab-GAPs in Regulating Autophagy

9. Methods for Measuring Autophagy Levels in Disease

TAKASHI ITOH AND MITSUNORI FUKUD

KANCHAN PHADWAL AND DOMINIC KURIAN

Introduction 144 RAB-GAPs Involved in Autophagy 147 Discussion 152 Acknowledgments 154 References 154

Introduction 196 Methods of Measuring Autophagy in Disease 198 Diseases 204 Emerging Trends 207 References 209

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10. Regulation of the DNA Damage Response by Autophagy VINAY V. EAPEN, DAVID P. WATERMAN, BRENDA LEMOS AND JAMES E. HABER

Introduction 214 The DNA Damage Response (DDR) in Higher Eukaryotes 215 Repair of DNA Damage 218 The Autophagy Pathway in Higher Eukaryotes 220 Autophagy and DNA Damage—A Complex Cross Talk 225 Conclusions and Perspectives 230 Acknowledgments 232 References 233

11. Autophagy and Cancer YOSHITAKA ISAKA, TOMONORI KIMURA, YOSHITSUGU TAKABATAKE AND ATSUSHI TAKAHASHI

Introduction 237 Cancer-Promoting Action of Autophagy 238 Cancer-Suppressing Action of Autophagy 240 Autophagy-Suppressing Drug 241 Autophagy-Suppressing Drug and Acute Kidney Injury 242 Conclusion 242 References 242

13. X-Box-Binding Protein 1 Splicing Induces an Autophagic Response in Endothelial Cells: Molecular Mechanisms in ECs and Atherosclerosis SOPHIA KELAINI, RACHEL CAINES, LINGFANG ZENG AND ANDRIANA MARGARITI

Introduction 260 Discussion 264 Summary 266 References 266

14. Small Molecule–Mediated Simultaneous Induction of Apoptosis and Autophagy SUDHAKAR JINKA AND RAJKUMAR BANERJEE

Introduction 270 Apoptosis 270 Autophagy 273 Cross Talk Between Apoptosis and Autophagy 274 Breast Cancer 276 PI3K-AKT-mTOR Signaling Pathway 276 Discussion 287 Acknowledgment 287 References 288

12. ULK1 Can Suppress or Promote Tumor Growth Under Different Conditions

15. Intestinal Autophagy Defends Against Salmonella Infection

TIAN MAO AND OUYANG LIANG

THOMAS A. PARKER AND KAILIANG JIA

Introduction 246 The Serine/Threonine Protein Kinase: ULK1 247 The Expression of ULK1 in Different Cancers 250 ULK1 Promote Tumor Growth 251 ULK1 Suppress Tumor Growth 252 Therapeutic Strategy for Targeting ULK1 in Cancers 253 Discussion 255 Acknowledgments 255 References 255

Introduction 291 Autophagy 292 Salmonella 293 Invasion of Salmonella Into Intestinal Epithelium Cells 295 Intestinal Autophagy in Host Defense Against Salmonella 297 Concluding Remarks 299 Acknowledgments 300 References 300

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16. Autophagy and LC3-Associated Phagocytosis Mediate the Innate Immune Response LARISSA D. CUNHA AND JENNIFER MARTINEZ

Autophagy as an Evolutionarily Conserved Survival Mechanism 304 Cross Talk Between Autophagy Machinery and Innate Immunity 305 Mechanisms of Selective Autophagy 313

Conclusions 318 References 318

Abbreviations and Glossary 321 Index 333

Foreword

This is the eleventh volume on Autophagy edited by Professor M.A. (Eric) Hayat and published by Elsevier, and like its predecessors, it addresses a wide range of topics in autophagy. Volume 11 of the multivolume series, Autophagy: Cancer, Other Pathologies, Inflammation, Immunity, Infection, and Aging, is organized into two sections: Molecular Mechanisms and Role in Disease. The first section provides an overview and covers methods for monitoring and modulating autophagy as well as specific applications. Autophagy is important in regulating hepatic lipid metabolism and cell cycle regulators, and its interaction with proteasomal degradation pathways is an emerging field of interest. The second section addresses a number of topics relating to the role of autophagy

in cancer, infection, atherosclerosis, and immune response. The number of publications on autophagy continues to expand as its many roles in health and disease are increasingly recognized, and new contexts are described. This issue brings out new insights on the relationship between the DNA damage response and autophagy, and like all of the chapters in this volume, promises to be exciting reading. This volume brings expert summaries of the state of the art, useful to both students and cognoscenti. Volume 11 represents an outstanding addition to this impressive series.

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Roberta A. Gottlieb, M.D. Cedars-Sinai Heart Institute


Foreword Intracellular protein turnover was established in 1940s; before that time, intracellular proteins were considered stable constituents. Christian De Duve discovered lysosomes in 1950s, and the first electron microscopic images of mitochondria inside lysosomes were published in the late 1950s. The importance of this finding was fully understood at that time, but now we know that these early micrographs illustrated autophagosomes containing mitochondria. The crucial contribution of lysosomes to the intracellular turnover was finally recognized in 1970s. Finally the role of autophagy in the constant recycling of intracellular constituents and organelles was demonstrated in 1990s, after the discovery of the genes and proteins that regulate autophagy, which has made it possible to monitor and manipulate the autophagic process and to generate knockout and transgenic animal models. This progress is well-demonstrated by the fact that in one of the seminal books on intracellular protein degradation, called Lysososmes: Their Role in Protein Degradation, edited by Hans Glaumann and F. John Ballard and published by Academic Press in 1987, the word “autophagy” is mentioned in the title of only 2 of the 20 chapters. The first book was published in 2003 by Landes Bioscience/Eurekah.com. The first journal devoted to autophagy, also called Autophagy, was established in 2005. Since that time, the number of scientific papers and books on autophagy has grown exponentially; also the present book series contributes to the exponential growth. Since

the slow start after the discovery of the first autophagosomes by electron microscopy in 1950s, autophagy finally receives the attention it deserves. For a long time, autophagy was considered to be nonselective, cytoplasmic constituents and organelles were thought to become randomly sequestered into autophagosomes for the delivery to lysosomes for degradation. Selective autophagy was first discovered in yeast cells, which have several well-known routes for the selective autophagy of different organelles and proteins. The existence of first molecular mechanisms and crucial roles of selective autophagy in mammalian cells were in fact an indication of selective removal of aggregate-prone proteins and damaged organelles, including mitochondria, especially in postmitotic cells such as neurons and muscle cells. This volume concentrates on the role of autophagy in disease. Both molecular mechanisms and roles in diseases are addressed by experts in the field. The field of autophagy still has many unanswered questions to address, and the topic is attracting an increasing number of scientists from different disciplines. This book will be welcomed by the newcomers as a concise overview of the current knowledge on autophagy. In addition, this volume will also offer the more experienced scientists working on other aspects of autophagy, an excellent way to update their knowledge on the role of autophagy in disease and health. Eeva-Liisa Eskelinen

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Preface

This is the eleventh volume of the multivolume series, Autophagy: Cancer, Other Pathologies, Inflammation, Immunity, Infection, and Aging, being published by Elsevier/ Academic Press; volumes 1–10 have been published. This volume, like other volumes in this series, discusses in detail most aspects of the autophagy machinery in the context of health, cancer, other pathologies, and cell death. Autophagy is a homeostatic process that plays a role in development and tissue homeostasis, including brain, adipose tissue, and blood vessels as described in this volume, as well as many other tissues covered in previous volumes. Impaired or dysregulated autophagy can contribute to various disease processes, including neurodegeneration, atherosclerosis, and cancer. Molecular mechanisms regulating autophagy in the context of disease are presented in this volume. Apoptosis is a common system of programmed cell death. Autophagy can be upregulated to avert apoptosis or promote apoptosis, but in other settings, autophagy can itself be a mechanism of programmed cell death. Alterations in apoptosis or autophagy are implicated in a wide variety of diseases. Excessive or impaired autophagy can result in increased cell death. It is known that the process of autophagy begins with the formation of a doublemembraned phagophore, encircling cellular components (e.g., misfolded proteins, damaged organelles or recyclable cytoconstituents), and forms an autophagosome.

Autophagosomes fuse with endosomes to form amphisomes, or with lysosomes to form autophagolysosomes (autolysosomes), where the cargo is degraded by hydrolytic enzymes (proteases, lipases, glycohydrolases) at acidic pH. Autophagy maintains homeostasis during starvation or stress conditions by balancing the synthesis of cellular components and their degradation. It serves to maintain healthy cells, tissues, and organs, but also enables survival of metastatic cancer cells and cells in the hypoxic core of a tumor. Chapter 1, Overview of Autophagy, reviews many aspects of the autophagy machinery, including underlying molecular mechanisms and its role in health and disease. This chapter also contains information on protein synthesis. The mechanisms responsible for protein folding and misfolding are explained, and the complex posttranslational modifications of proteins, particularly autophagy-related proteins, are discussed. These concepts regarding the conformational modifications of proteins are a prerequisite to understanding the removal of unfolded, misfolded, incompletely folded, or aggregated proteins by autophagy and other mechanisms. Also discussed is selective autophagy that degrades large intracellular aggregates and pathogens, dysfunctional organelles, or parts of them. The differences between nonselective (bulk autophagy) and selective modes of autophagic sequestration are explained. Selective autophagy is further categorized

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into exclusive and nonexclusive autophagy. Fifteen types of selective autophagies are discussed. Failure of selective autophagy is linked to specific diseases, depending on the target. Pharmacological induction of global autophagy has been proposed as a treatment for these disorders, although upregulation of selective autophagy remains an unmet need. A large number of autophagy functions and abbreviations of commonly used terms are included. The role of autophagy in aging is also detailed in this chapter. It is known that “there is no birth without death and there is no death without birth.” Aging progression cannot be prevented, but it can be delayed. Therefore suggestions are offered to prolong healthy life span, but discipline is required to achieve this goal. Translation of autophagy control to the clinical environment has remained inadequate. The recent advances in measuring and modeling autophagic flux and the entire autophagy system are presented. Autophagy and apoptosis are the two key programmed cell death pathways, without affecting the surrounding cells. These pathways play an important role not only in development and morphogenesis but also in various diseases such as cardiovascular and infectious diseases and cancer (e.g., breast cancer). It is important to understand the mechanism of lipid metabolism in the context of metabolic disorders. Two major proteolytic degradation pathways (autophagy and proteasome) are mutually regulated and play a key role in modulating cellular lipid homeostasis. These two pathways are linked together by the REGγ-SirT1 complex. It is suggested that this complex is a promising therapeutic target for the treatment of metabolic disorders such as type 2 diabetes, obesity, and liver steatosis. Cyclin A2 is an essential regulator of the cell cycle, and its degradation by the

ubiquitin–proteasome system (UPS) is well known. Autophagy is an additional pathway for cyclin A2 degradation, and the application of live-cell imaging in this context is emphasized here. The role of autophagosomes in the functioning of autophagy is well known. It is also known that a variety of proteins are required for membrane trafficking and formation of autophagosomes. Rab small GTPases are key regulators of membrane trafficking. An overview of the proposed functions of Rab-GAPs in the autophagosome formation is presented in this volume. Accumulation of disease-causing proteins is a hallmark of a number of neurodegenerative disorders, including Parkinson’s and Alzheimer’s diseases. Treatment options that effectively prevent the development of misfolded and aggregated proteins represent important disease-modifying therapeutic candidates. In this connection the role of HDAC inhibitors in the modulation of the expression of several disease proteins is explained in this volume. The role of autophagy-related genes during autophagosome biogenesis is explained. Atg9 protein, for example, acts as a recruitment hub for several other Atg proteins at the site of autophagosomes formation, and thus plays a central role in autophagy regulation. Autophagy field has greatly advanced in the diverse areas of biology and medicine, and a multitude of assay methods have been and are being developed. It is imperative to assess the quality and robustness of these methods used in the autophagy detection. Some of the widely used assay methods to study autophagy both in vitro and in vivo models are presented in this volume, especially with emphasis on disease states. Also, assay reagents/kits for autophagy are discussed. The DNA damage due to environmental stresses triggers a highly conserved

Preface

signaling cascade that enforces cell cycle arrest and promotes the repair of DNA lesions. The autophagy pathway aids cellular survival in conditions of poor nutrient availability by scavenging internal reserves of macromolecules (proteins) in order to recycle molecular building blocks and damaged organelles in order to recycle molecular building blocks. An attempt is made in this volume to review the connection between the DNA damage response and autophagy, emphasizing the molecules that mediate such cross talk. The antitumor or pro-tumor role of autophagy is well known. Cancers can use autophagy to survive under metabolic stresses. To counter this, a combination therapy of chloroquine and anticancer drugs can be used. The autophagy-modulating therapy for cancer is addressed in this volume. The mammalian homology of Atg1 (ULK1) protein is not only involved in the initial autophagic process but also the exclusive serine/threonine protein kinase so far identified in the core autophagic pathway. The activation of ULK1 by upstream signals (AMPK and mTOR) can trigger autophagy under different stress conditions. ULK1, FIP200, mAtg13, and Atg101 form a protein complex that can be regulated by posttranslational modifications (e.g., phosphorylation). Both the transcriptional regulations of ULK1 complex and posttranscriptional modifications of it vary in different cancer types. ULK1 can either promote tumor development or suppress tumor growth based on distinct relevant conditions. Smallmolecule compounds that can target ULK1 with antitumor capacities are discussed. Atherosclerosis is the leading cause of death in the developed countries. It begins with the production of a plaque in the artery wall, limiting blood flow. Autophagy occurs in severe atherosclerotic plaques, implicating macrophages and vascular smooth

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muscle cells. It is still debated whether autophagy is a damaging or a protective mechanism or a balance of both is needed for normal cellular function. However, it is known that X-Box binding protein 1 (XBP1) mRNA splicing is involved in regulating autophagy in endothelial cells through Beclin 1 transcriptional activation. It is pointed out that sustained activation of XBP1 results in the apoptosis of these cells and development of atherosclerosis. Recent evidence shows the importance of XBP1 eliciting an autophagy response in the endothelial cells. Retinal pigment epithelial cells (RPECs) are continuously subjected to endogenous and exogenous oxidative injury. This injury to the RPECs causes loss of these cells, leading to retinal degeneration. However, usually this loss occurs late in life because these cells are resistant to oxidative stress. Autophagy is involved in cellular homeostasis of retinal pigment epithelium and thus ensures the functional integrity of the retina. It is explained that autophagy regulates functional pathways associated with ocular pathological conditions, including aged macular degeneration that is associated with the loss of RPECs. Autophagy is an essential component in both innate and adaptive immunity. An interplay exists between autophagy-mediated resistance and pathogen virulence factors that attempt to subvert autophagic machinery. In the case of Salmonella infection, autophagy is essential to restrict bacterial survival in the host intestinal epithelial cells. The mechanism underlying defending against this infection is explained in this volume. Autophagy functions as a means of protein and organelle quality control. Autophagy, in addition to recycling intracellular macromolecules and organelles, plays a crucial role in defense of the cell against

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Preface

intracellular pathogens in conjunction with immune response and inflammation. Thus, autophagy serves as a primordial response to both endogenous and exogenous distresses. For the convenience of the readers, the contents are divided into two major sections: Molecular Mechanisms and Diseases. By bringing together a large number of experts (oncologists, physicians, medical research scientists, and pathologists) in the field of autophagy, it is my hope that substantial progress will be made against the terrible diseases that afflict humans. It would be nigh impossible for a single author to cover the current state of knowledge of this exceedingly complex process of autophagy. The participation of multiple authors allows for the presentation of different points of view on controversial aspects of the role of autophagy in health and disease. This volume was written by 38 contributors representing 9 countries. I am grateful to them for their promptness in accepting my suggestions. Their practical experience highlights the very high quality of their writings, which should build and further the endeavors of the readers in this important medical field. I respect and appreciate the hard work and exceptional insight into the role of autophagy in disease provided by these contributors.

It is my hope that subsequent volumes of this series will join this volume in assisting in the more complete understanding of the complex process of autophagy and eventually in the development of therapeutic applications. There exists a tremendous urgent demand by the public and the scientific community to develop better treatments for major diseases. In the light of the human impact of these untreated diseases, government funding must give priority to researching cures over global military superiority. I am grateful to Dr. Roberta Gottlieb, MD, for composing the poems that describe the process of Autophagy with appropriate humor, contributing the Foreword, and valuable suggestions for improving the quality of the writing. I greatly appreciate thoughtful help extended to me by Linda VersteegBuschman, the senior editor at Elsevier, before and during the publication of this series. I offer thanks to President Dawood Farahi for recognizing the importance of medical research and publishing through an institution of higher education. I am thankful to Danielle Antonucci and Anyelina Nunez and my students for their contributions to the final preparation of this volume. April, 2016 M. A. Hayat

Contributors

Henning Arlt Department of Cell Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

Larissa D. Cunha Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN, United States

Rajkumar Banerjee Biomaterials Group, CSIR-Indian Institute of Chemical Technology, Habsiguda, Telangana, India

Rachel Caines Centre for Experimental Medicine, Queen’s University Belfast, Belfast, United Kingdom

Andre Du Toit Department of Physiological Sciences, Faculty of Natural Sciences, University of Stellenbosch, Stellenbosch, South Africa

Vinay V. Eapen Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States

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Contributors

Mitsunori Fukuda Laboratory of Membrane Trafficking Mechanisms, Department of Developmental Biology and Neurosciences, Graduate School of Life Sciences, Tohoku University, Miyagi, Japan

Roberta A. Gottlieb Molecular Cardiobiology, Cedars-Sinai Heart Institute, Barbra Steisand Women’s Heart Center, Los Angeles, CA, United States

James E. Haber Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States

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M.A. (Eric) Hayat Kean University, Union, NJ, United States

Jan-Hendrik S. Hofmeyr Department of Biochemistry, Faculty of Natural Sciences, University of Stellenbosch, Stellenbosch, South Africa

Yoshitaka Isaka Department of Nephrology, Osaka University Graduate School of Medicine, Osaka, Japan


Contributors

Takashi Itoh Center for Frontier Oral Science, Graduate School of Dentistry, Osaka University, Osaka, Japan

Kailiang Jia Department of Biological Sciences, Florida Atlantic University, Boca Raton, FL, United States

Sudhakar Jinka Biomaterials Group, CSIRIndian Institute of Chemical Technology, Habsiguda, Telangana, India

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Sophia Kelaini Centre for Experimental Medicine, Queen’s University Belfast, Belfast, United Kingdom

Yeon A. Kim Department of Ophthalmology, Dong-A University College of Medicine, Busan, South Korea

Tomonori Kimura Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States


Contributors

Dominic Kurian Neurobiology Division, The Roslin Institute R(D)SVS, University of Edinburgh, Midlothian, United Kingdom

Yoon H. Kwon Department of Ophthalmology, Dong-A University College of Medicine, Busan, South Korea

Brenda Lemos Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States

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Xiaotao Li Department of Molecular and Cellular Biology; Department of Medicine, The Dan L. Duncan Cancer Center, The Diabetes Research Center, Baylor College of Medicine, Houston, TX, United States

Lei Li Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences, East China Normal University, Shanghai, China

Ouyang Liang State Key Laboratory of Biotherapy, Sichuan University, Chengdu, PR China


Contributors

Ben Loos Department of Physiological Sciences, Faculty of Natural Sciences, University of Stellenbosch, Stellenbosch, South Africa

Abdelhalim Loukil Institut de Génétique Moléculaire de Montpellier (IGMM), CNRS UMR 5535, Montpellier, France

Tian Mao State Key Laboratory of Biotherapy, Sichuan University, Chengdu, PR China

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Andriana Margariti Centre for Experimental Medicine, Queen’s University Belfast, Belfast, United Kingdom

Jennifer Martinez Immunity, Inflammation, and Disease Laboratory, National Institute of Environmental Health Sciences, Research Triangle Park, NC, United States

Thomas A. Parker Department of Biological Sciences, Florida Atlantic University, Boca Raton, FL, United States


Contributors

Marion Peter Institut de Génétique Moléculaire de Montpellier (IGMM), CNRS UMR 5535, Montpellier, France

Kanchan Phadwal Neurobiology Division, The Roslin Institute R(D)SVS, University of Edinburgh, Midlothian, United Kingdom

Fulvio Reggiori Department of Cell Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

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Yoshitsugu Takabatake Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States

Atsushi Takahashi Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States

Elizabeth A. Thomas Department of Molecular and Cellular Neuroscience, The Scripps Research Institute, La Jolla, CA, United States


Contributors

David P. Waterman Department of Biology, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, United States

Young H. Yoo Department of Anatomy and Cell Biology and Mitochondria Hub Regulation Center, Dong-A University College of Medicine, Busan, South Korea

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Lingfang Zeng Cardiovascular Division, King’s College London, London, United Kingdom


Autophagy: Volume 1—Contributions Mechanisms of Regulation of p62 in Autophagy and Implications for Health and Diseases Molecular Mechanisms Underlying the Role of Autophagy in Neurodegenerative Diseases Roles of Multiple Types of Autophagy in Neurodegenerative Diseases Autophagy and Crohn’s Disease: Towards New Therapeutic Connections The Role of Autophagy in Atherosclerosis Treatment of Diabetic Cardiomyopathy through Upregulating Autophagy by Stimulating AMP-Activated Protein Kinase Hyperglycemia-Associated Stress Induces Autophagy: Involvement of the ROSERK/JNK-P53 Pathway Role of Autophagy in the Cellular Defense Against Inflammation Mytophagy Plays a Protective Role in Fibroblasts from Patients with Coenzyme Q10 Deficiency Presence of Dioxin Kidney Cells Induces Cell Death with Autophagy Molecular Mechanisms Underlying the Activation of Autophagy Pathways

by Reactive Oxygen Species and their Relevance in Cancer Progression and Therapy Induction of Autophagic Cell Death by Anticancer Agents Immunogenicity of Dying Cancer Cells—The Inflammasome Connection Autophagic Death Arrives to the Scene Selenite-Mediated Cellular Stress, Apoptosis and Autophagy in Colon Cancer Cells Enhancement of Cell Death in High Grade Glioma Cells: Role of N-(4-Hydroxyphenyl) RetinamideInduced Autophagy Cisplatin Exposure of Squamous Cell Carcinoma Cells Leads to the Modulation of Autophagic Pathway Autophagy, Stem Cells and Tumor Dormancy Death-Associated Protein Kinase 1 Suppresses Tumor Growth and Metastasis via Autophagy And Apoptosis TRIM13, Novel Tumor Suppressor: Regulator of Autophagy and Cell Death Hypoxia-Induced Autophagy Promotes Tumor Cell Survival

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Autophagy: Volume 2—Contributions Selective Autophagy: Role of Interaction Between the Atg8 Family Mammalian Autophagy Can Occur Through an Atg5/Atg7-Independent Pathway Selective Autophagy: Role of Ubiquitin and Ubiquitin-Like Protein in Targeting Protein Aggregates, Organelles, and Pathogen Ubiquitin and p62 in Selective Autophagy in Mammalian Cells Role of the Golgi Complex and Autophagosome Biogenesis in Unconventional Protein Secretion Induction of Autophagy in HIV-1Uninfected Cells: Role of Fusogenic Activity of GP41 Non-Lipidated LC3 Is Essential for Mouse Hepatitis Virus Infection Suppression of Innate Antiviral Immunity after Hepatitis C Virus Infection: Role of the Unfolded Protein Response and Autophagy Mycobacterial Survival in Alveolar Machophages as a Result of Coronin-1A Inhibition of Autophagosome Formation Virulent Mycobacteria Upregulate Interleukin-6 (IL-6) Production to Combat Innate Immunity Autophagy in Parasitic Protists Cell Surface Pathogen Receptor CD46 Induces Autophagy Helicobacter Pylori Infection and Autophagy: A Paradigm for Host– Microbe Interactions

Autophagy Is Required During MonocyteMacrophage Differentiation Role of Autophagy Gene Atg5 in T Lymphocyte Survival and Proliferation Sepsis Induced Autophagy Is a Protective Mechanism Against Cell Death Blockage of Lysosomal Degradation Is Detrimental to Cancer Cells Survival: Role of Autophagy Activation Autophagy as a Sensitization Target in Cancer Therapy Pathogenesis of Bile Duct Lesions in Primary Biliary Cirrhosis: Role of Autophagy Followed by Cellular Senescence Autophagy and NADPH Oxidase Activity Tends to Regulate Angiogenesis in Pulmonary Artery Endothelial Cells With Pulmonary Hypertension Role of Autophagy in Heart Disease Regulation of Autophagy in ObesityInduced Cardiac Dysfunction Cytochrome P4502E1, Oxidative Stress, JNK, and Autophagy in Acute Alcohol-Induced Fatty Liver Autophagy-Independent Tumor Suppression: Role of UVRAG Chaperone-Mediated Autophagy and Degradation of Mutant Huntingtin Protein The Role of Atg8 Homologue in Lewy Disease

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Autophagy: Volume 3—Contributions Autophagic Flux, Fusion Dynamics and Cell Death Architecture of the ATG12-ATG5-ATG16 Complex and Its Molecular Role in Autophagy The Molecular Mechanisms Underlying Autophagosome Formation in Yeast Role Of Autophagy In Cell Survival In Liver Injury Polymorphisms in Autophagy-Related Genes in Crohn’s Disease: Impact on Intracellular Bacteria Persistence and Inflammatory Response Functional Relevance of Autophagins in Life and Disease Strategies to Block Autophagy in Tumour Cells Autophagic Dysfunction in Gaucher Disease and Its Rescue by Cathepsin B and D Proteases Cargo Recognition Failure Underlies Macroautophagy Defects in Huntington’s Disease Hepatitis C Virus Infection, Autophagy and Innate Immune Response Geranylgeranoic Acid Induces Incomplete Autophagy but Leads to the Accumulation of Autophagosomes in Human Hepatoma Cells Defense Against Proteotoxic Stress in the Heart: Role of p62, Autophagy, and Ubiquitin-Proteasome system

Elimination of Intracellular Bacteria by Autophagy Protein Phosphatase 2A Has Positive and Negative Roles in Autophagy Erufosine Induces Autophagy and Apoptosis in Oral Squamous Cell Carcinoma: Role of the Akt-mTOR Signaling Emerging Role of Hypoxia-Induced Autophagy in Cancer Immunotherapy Involvement of Autophagy and Apoptosis in Studies of Anticancer Drugs Autophagy-Based Protein Biomarkers for In Vivo Detection of Cardiotoxicity in the Context of Cancer Therapy Inhibition of mTOR Pathway and Induction of Autophagy Block Lymphoma Cell Growth: Role of AMPK Activation Autophagy Regulates Osteoarthritis-Like Gene Expression Changes: Role of Apoptosis and Reactive Oxygen Species The Key Role of Autophagy and Its Relationship with Apoptosis in Lepidopteran Larval Midgut Remodeling Interferon Regulatory Factor 1 Regulates Both Autophagy and Apoptosis in Splenocytes During Sepsis The Interplay Between Autophagy and Apoptosis

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Autophagy: Volume 4—Contributions Molecular Process and Physiological Significance of Mitophagy Principles of Mitophagy and Beyond Quality Control in Mitochondria Mitophagy: An Overview Mitophagy Induction and CurcuminMediated Sonodynamic Chemotherapy Role of Nix in the Maturation of Erythroid Cells Through Mitochondrial Autophagy Role of the Antioxidant Melatonin in Regulating Autophagy and Mitophagy Ubiquitin Ligase-Assisted Selective Autophagy of Mitochondria: Determining Its Biological Significance Using Drosophila Models Atg32 Confers Selective Mitochondrial Sequestration as a Cargo for Autophagy

PARK2 Induces Autophagy Removal of Impaired Mitochondria via Ubiquitination Ubiquitination of Mitofusins in PINK1/ Parkin-Mediated Mitophagy Mitochondrial Alterations and Mitophagy in Response to Hydroxydopamine Role of Mitochondrial Fission and Mitophagy in Parkinson’s Disease Mitophagy Controlled by the Pink1-Parkin Pathway Is Associated With Parkinson’s Disease Pathogenesis Loss of Mitochondria During Skeletal Muscle Atrophy Role of Impaired Mitochondrial Autophagy in Cardiac Aging: Mechanisms and Therapeutic Implications

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Autophagy: Volume 5—Contributions Molecular Crosstalk Between the Autophagy and Apoptotic Networks in Cancer Inhibition of ErbB Receptors and Autophagy in Cancer Therapy Ginsenoside F2 Initiates an Autophagic Progression in Breast Cancer Stem Cells Role of Autophagy in Cancer Therapy Autophagy in Human Brain Cancer: Therapeutic Implications Blockage of Lysosomal Degradation Is Detrimental to Cancer Cells Survival: Role of Autophagy Activation Induction of Protective Autophagy in Cancer Cells by an NAE Inhibitor MLN4924 Effect of Autophagy on ChemotherapyInduced Apoptosis and Growth Inhibition Autophagy Upregulation Reduces Doxorubicin-Induced Cardiotoxicity

Autophagy in Critical Illness Autophagy in the Onset of Atrial Fibrillation Role of Autophagy in Atherogenesis Regulation of Autophagy in Insulin Resistance and Type 2 Diabetes Pancreatic Beta Cell Autophagy and Islet Transplantation Autophagy Guards Against Immunosuppression and Renal Ischemia-Reperfusion Injury in Renal Transplantation When the Good Turns Bad: Challenges in the Targeting of Autophagy in Neurodegenerative Diseases The α-Tubulin Deacetylase HDAC6 in Aggresome Formation and Autophagy: Implications for Neurodegeneration

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Autophagy: Volume 6—Contributions Regulation of Autophagy by Amino Acids Regulation of Autophagy by Amino Acid Starvation Involving Ca2+ Regulation of Autophagy by microRNAs Mechanisms of Cross-Talk Between Intracellular Protein Degradation Pathways Cross-Talk Between Autophagy and Apoptosis In Adipose Tissue: Role of Ghrelin Intracellular Pathogen Invasion of the Host Cells: Role of the ALFA-Hemolysin Induced Autophagy Modulation of Autophagy by Herpesvirus Proteins Autophagy Induced by Varicella-Zoster Virus and the Maintenance of Cellular Homeostasis Autophagy and Hepatitis B Virus Toll-Like Receptors Serve as Activators for Autophagy in Macrophages Helping to Facilitate Innate Immunity

Autophagy in Antigen Processing for MHC Presentation to T Cells Autophagy Controls the Production and Secretion of IL-1β: Underlying Mechanisms Role of Autophagy in P2x7 ReceptorMediated Maturation and Unconventional Secretion of IL-1β in Microglia Autophagy Restricts Interleukin-1β Signaling via Regulation of p62 Stability The Role of Autophagy in the Thymic Epithelium The Role of Autophagy Receptors in Mitophagy The Role of Parkin and PINK1 in Mitochondrial Quality Control Autophagy Degrades Endocytosed Gap Junctions

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Autophagy: Volume 7—Contributions Role of Endoplasmic Reticulum in the Formation of Phagophores/ Autophagosomes: Three-Dimensional Morphology The Nucleus-Vacuole Junction in Saccharomyces cerevisiae Human WIPIS as Phosphoinositide Effectors at the Nascent Autophagosome: A Robust Tool To Assess Macroautophagy by Quantitative Imaging Induction of Autophagy: Role of Endoplasmic Reticulum Stress and Unfolded Protein Response Atg 16L1 Protein Regulates Hormone Secretion Independent of Autophagy Macroautophagy of Aggregation-Prone Proteins in Neurodegenerative Disease Lithium Ameliorates Motor Disturbance by Enhancing Autophagy in Tauopathy Model Mice

Beta-Asarone Reduces Autophagy in a Dose-Dependent Manner and Interferes with Beclin-1 Function Apoptosis and Autophagy: The Yin-Yang of Homeostasis in Cell Death in Cancer Role of Autophagy and Apoptosis in Odontogenesis Autophagy Is Required During MonocyteMacrophage Differentiation Degradation of HSPGs Enhances LOX-1Mediated Autophagy The Presence of LC3 and LAMP1 Is Greater in Normal Sino-Atrial Nodal Cells than in Ordinary Cardiomyocytes, Indicating a Constitutive Event Regulation of (Macro)-Autophagy in Response to Exercise Cigarette Smoke Promotes Cancer via Autophagy

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Autophagy: Volume 8—Contributions Role of the Beclin-1 Network in the CrossRegulation Between Autophagy and Apoptosis Role of SIRT1 as a Regulator of Autophagy Apoptosis Blocks Beclin 1-Dependent Autophagosome Synthesis Is Selective Autophagy Distinct from Starvation-Induced Autophagy? Molecular Mechanisms Underlying Cell Death Caused By Cationic Polymers The Role of Autophagy in Cell Death The Role of Autophagy and Mitophagy in Mitochondrial Diseases Autophagy Regulation by HMGb1 Disease Autophagy Defects and Lafora Disease Regulation of Autophagy in Parkinson’s Disease: Insights into New Therapeutic Targets

Role of Autophagy in Cancer Development via Mitochondrial Reactive Oxygen Species Role of Autophagy in Cancer Therapy The Role of Autophagy in Cancer and Chemotherapy Autophagy Activation in the Tumor Microenvironment: A Major Process in Shaping the Anti-Tumor Immune Response Omega-3 DHA and EPA Conjugates Trigger Autophagy Through PPARγ Activation in Human Breast Cancer Cells Pro-Oxidative Phytoagents Induce Autophagy in Tumors: Villain or Benefactor in Cancer Treatment?

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Autophagy: Volume 9—Contributions Autophagic Structures in Yeast Mitophagy: Sensors, Regulators, and Effectors Regulation of Autophagy by ActinAssociated Signalling Pathways G2019S Mutation of LRRK2 increases autophagy via MEK/ERK pathway Cargo Proteins Facilitate the Formation of Transport Vesicles, but not Autophagosomes Absence of Bax and Bak: Implications of Autophagy and Alternative Mitochondrial Functions The Antiapoptotic Protein BCL-2 Has Also an Antiautophagy Role Through Beclin 1 Inhibition Organic Pollutant Perfluorooctane Sulfonate-Induced Lysosomal Membrane Permeabilization Blocks Autophagy Flux in Human Hepatoma Cells Mutant p53 Located in the Cytoplasm Inhibits Autophagy Role of Autophagy in Regulation Survival or Death of Cancer Cells Regulation of Autophagy in Chronic Lymphocytic Leukemia: The Role of Histone Deacetylase Inhibitors

Improving the Survival of Mesenchymal Stromal Cells Against Oxidative Stress in Transplantation: Role of Autophagy Induction Low-Density Lipoprotein ReceptorRelated Protein 1 Mediates Vacuolating Cytotoxin-Induced Autophagy and Apoptosis During Helicobacter pylori Infection Cytomegalovirus Blocks Autophagy During Infection of the Retinal Pigment Epithelial Cells: Functional Relationship Between Autophagy and Apoptosis Unusual Functions for the Autophagy Machinery in Apicomplexan Parasites Subversion of Innate Phagocytic Cells in orientia tsutsugamushi Intracellular Bacterium Anaplasma phagocytophilum Induces Autophagy by Secreting Substrate Ats-1 that Neutralizes the Beclin 1-Atg14l Autophagy Initiation Pathway Host Autophagy in Antifungal Immunity

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Autophagy: Volume 10—Contributions Molecular Mechanisms Underlying the Degradation of Peroxisomes Role of Poly (ADP-Ribose) in Catalyzing Starvation-Induced Autophagy Cross-Talk Between Autophagy and Death Receptor Signaling Pathways Role of Autophagy in Mammalian Embryogenesis: Response to Developmental Programs Autophagy in Adipose Tissue Prevention of Adverse Metabolic Consequences of Adipocyte Dysfunction Using MR Antagonists A Rapid Method for Detecting Autophagy Activity in Live Cells Using Cellometer Image Cytometry

CDC37: Implications in Regulation of Kinases and Proteins Linked to Neurodegenerative and Other Diseases Autophagy in the Degeneration of Optic Nerve and Spinal Cord Axons Membrane Type-1 Matrix MetalloproteinaseRegulated Autophagy: A Role in Brain Cancer Chemoresistance Induction of Autophagy and Apoptosis in Melanoma Treated with Palladacycle Complexes Autophagy in Atherosclerosis

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P A R T

I

MOLECULAR MECHANISMS 1 Overview of Autophagy 3 2 Methods for Measuring Autophagosome Flux—Impact and Relevance 91 3 Loss of Pigment Epithelial Cells Is Prevented by Autophagy 105 4 Role of Autophagy Inhibition in Regulating Hepatic Lipid Metabolism: Molecular Cross Talk Between Proteasome Activator REGγ and SirT1 Signaling 119 5 Role of Autophagy in Regulating Cyclin A2 Degradation: Live-Cell Imaging 133 6 Roles of Rab-GAPs in Regulating Autophagy 143 7 The Role of Histone Deacetylase Inhibition in the Accumulation and Stability of Disease-Related Proteins 159 8 The Role of Atg9 in Yeast Autophagy 181


C H A P T E R

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Overview of Autophagy M.A. Hayat O U T L I N E Specific Functions of Autophagy (A Summary) Autophagy Process

Beclin 1 Nonautophagic Functions of Autophagy-Related Proteins Microtubule-Associated Protein Light Chain 3

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Autophagy in Normal Mammalian Cells 10 Endoplasmic Reticulum ER Stress

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Autophagic Flux

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Autophagic Lysosome Reformation

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Autophagy as a Double-Edged Sword

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Protein Synthesis 19 Methods 24 Abnormal Proteins 24 Molecular Chaperones 26 The ER 26 ER and Apoptosis 27 Autophagic Proteins Protein Degradation Systems

M.A. Hayat (ed): Autophagy, Volume 11. DOI: http://dx.doi.org/10.1016/B978-0-12-805420-8.00001-9

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Aggrephagy 31 Aggresome, Ubiquitin Proteasome, and Autophagic Systems 32

Major Types of Autophagies 13 Macroautophagy (Autophagy) 14 Microautophagy 14 Chaperone-Mediated Autophagy 14 Autophagosome Formation

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Monitoring Autophagy

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Reactive Oxygen Species

33

Mammalian Target of Rapamycin

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Role of Autophagy in Tumorigenesis and Cancer

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Autophagy and Immune System

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Autophagy and Senescence

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Role of Autophagy and Cellular Senescence in Aging Role of mTOR Response by mTOR and Autophagy to Dietary Restriction Role of Sirtuins Role of Stem Cells Role of Cellular Senescence

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39 41 42 42 43 43

© 2017 2016 Elsevier Inc. All rights reserved.

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1. Overview of Autophagy

Effect of Aging on Skeletal Muscle 44 Role of Autophagy in Heart Disease 45 Role of Autophagy in Huntington’s Disease 45 Role of Autophagy in Alzheimer’s Disease 45 Role of Autophagy in Macular Degeneration 45 Role of Autophagy in Viral Defense and Replication

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Role of Autophagy in Intracellular Bacterial Infection

47

Role of Autophagy in Heart Disease

48

Role of Autophagy in Neurodegenerative Diseases

49

Mitochondrial Fusion and Fission

Selective Autophagy 56 Allophagy 58 Axonophagy (Neuronal Autophagy) 59 Chromatophagy 60 Ciliophagy 61 Crinophagy 62 Exophagy 62 Glycophagy 64 Lipophagy 65 Lysophagy 67 Mitophagy 67 Nucleophagy 68 Pexophagy 69 Role of Pexophagy in Yeast

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Autophagy and Necroptosis

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70

Reticulophagy 72 Ribophagy 73 Xenophagy 74 Zymophagy 75

Cross Talk Between Autophagy and Apoptosis 51 Autophagy and Ubiquitination

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References 75

Abstract

Autophagy plays a direct or an indirect role in health and disease. A simplified definition of autophagy is that it is an exceedingly complex process that degrades modified, superfluous (surplus), or damaged cellular macromolecules and whole organelles using hydrolytic enzymes in the lysosomes. It consists of sequential steps of induction of autophagy, formation of autophagosome precursor, formation of autophagosomes, fusion between autophagosome and lysosome, degradation of cargo contents, efflux transportation of degraded products to the cytoplasm, and lysosome reformation. This chapter discusses specific functions of autophagy, the process of autophagy, major types of autophagy, influences on autophagy, and the role of autophagy in disease, immunity, and defense.

Aging has so permeated our lives that it cannot be stopped, but it can be delayed. Under the circumstances, time is our only friend. Because aging process is accompanied by disability and disease (e.g., Alzheimer’s and Parkinson’s conditions) and cannot be prevented, it seems that slow aging is the only way to have a healthy longer life. In general, aging can be slowed down by not tobacco smoking or chewing, preventing or minimizing perpetual stress (anger, competition), and abstinence from alcoholic beverages, practicing regular exercise and sleep, and having a healthy diet. Living a longer life accompanied by a disability (disease) is of less importance than achieving a healthy longer life by delaying the aging

I. MOLECULAR MECHANISMS

OVERVIEW OF AUTOPHAGY

5

process. The direct or indirect role of autophagy in affecting the health and disease by the above-mentioned factors is summarized here. Cigarette smoking impairs the function of most tissues and organs in the body. One of the serious results of smoking is chronic obstructive pulmonary disease (COPD) (WHO, November 25, 2015), which is the third leading cause of death worldwide (Rennard and Drummond, 2015). More than 15% of smokers suffer from COPD and most develop some degree of pulmonary impairment (Truedsson et al., 2016). COPD is a heterogeneous inflammatory disease characterized by different phenotypes, including airflow limitation (not fully reversible), chronic sputum production (chronic bronchitis), and destruction of lung tissue (emphysema) (Rennard and Drummond, 2015). COPD is associated not only with acute exacerbations but also with comorbidities such as cardiovascular disease and lung cancer (Decramer and Janssens, 2013). A number of studies have been carried out for identifying biomarkers for early signs of COPD in smokers and ex-smokers (Truedsson et al., 2016). Biomarkers are highly important for achieving personalized medicine. Circulating protein biomarkers of COPD have been identified in blood for diagnosing the disease and treatment assessment (Merali et al., 2014; Truedsson et al., 2016). Plasma fibrinogen and CRP are elevated in COPD patients. However, expiratory volume in 1 s is most important for evaluating the disease severity with increasing airflow limitation. Stress is one of the environmental (exogenous) factors that directly or indirectly contributes to some of the human age–related diseases; Alzheimer’s disease (AD) is one of the examples. Recently, it was reported that stress can increase the production of amyloid beta (AB) in mice brains (Park et al., 2015). They obtained this information by restraining mice to induce acute stress. They also obtained increased amyloid levels by treating mice with primary neuronal cells and human neuroblastoma cells with corticotrophin-releasing factor (CRF); this hormone mediates stress in mice and humans. CRF binds to CRF receptor 1 that gets internalized and recruits the enzyme γ-secretase to lipid rafts where it can generate AB. However, there also is a receptor-independent pathway in this operation, indicating the complexity of this system, which explains the reason why some receptor antagonist drugs show ambivalent results in patients. There is no doubt that regular physical activity is associated with a reduced risk of mortality and contributes to the primary and secondary prevention of many types of diseases. Alcohol is the most abused substance worldwide. More than 18 million adults are affected by alcoholism in the United States, which costs 27 billion dollars for treating alcohol-attributable diseases (National Institute on Alcohol Abuse and Alcoholism). Alcoholic liver disease is a major cause of death in the United States (and some other countries), resulting in the death of approximately 26,000 persons/year, and 46% of which is associated with alcohol abuse (Yoon and Yi, 2010). The detrimental effects of alcohol use on liver and skeletal muscle have been studied extensively. Alcohol abuse often leads to liver injury associated with alcoholic hepatitis, liver fibrosis, cirrhosis, and liver cancer (Gao and Bataller, 2011). The impairment of protein synthesis and degradation occur in alcohol-exposed liver cells, accompanied by changes in energy balance. For example, liver enlargement (hepatomegaly) is common in alcoholics; the increased hepatic mass arises from the accumulation of proteins and lipids. Alcohol impairs skeletal muscle protein synthesis. Inadequately folded or misfolded proteins


6


accumulate and energy-generating mitochondria are damaged by alcohol abuse. One of the defense mechanisms mounted by cells against the toxic effects of alcohol is autophagy. It is known that autophagy maintains a balance among the processes of protein, lipid, and carbohydrate synthesis, degradation, and recycling. Autophagy generally plays a protective role against the toxic effects of alcohol consumption; examples include liver diseases (Yang et al., 2014a), pancreatitis (Fortunato et al., 2009), and brain neurotoxicity (Chen et al., 2012a). In contrast, autophagy is detrimental to some of the alcohol-induced diseases, including heart contractile dysfunction (Guo et al., 2012) and chronic skeletal muscle dysfunction (Thapaliya et al., 2014). Patients with alcoholic cirrhosis and hepatitis show severe muscle loss. The main purpose of the following comments is to explain the role of physical exercise through autophagy in human health. Exercise is a potent inducer of autophagy. It is well known that generally physical exercise has beneficial effects on human health. Exercise, for example, contributes to increased healthy life span, and protection against cancer, cardiovascular, inflammatory, and neurodegenerative diseases. Exercise also exerts protection against metabolic disorders such as diabetes (Handschin and Spiegelman, 2008). It has been reported that defective hepatic autophagy in obesity promotes ER stress (discussed elsewhere in this chapter) and causes insulin resistance (Yang et al., 2010). Stress, in turn, increases autophagy levels, permitting cells to adapt to changing nutritional and energy demands primarily through protein catabolism (Kuma and Mizushima, 2010). Acute exercise induces autophagy in skeletal and cardiac muscles. Exercise-induced autophagy in vivo involves disruption of the BCL2-beclin 1 complex (He et al., 2012b). BCL2 is an antiapoptotic and antiautophagy protein, and is a crucial regulator of exercise- and starvation-induced autophagy, which may contribute to the beneficial metabolic effects of exercise. It is known that normal physical exercise activates autophagy in skeletal muscles. Proper regulation of the autophagic flux is fundamental for homeostasis of skeletal muscle in physiological conditions and in response to stress (Grumati et al., 2011). Upregulation of autophagy-regulatory genes after exercise is related to an increased autophagic flux (Jamart et al., 2011). Impairment of the autophagic flux causes accumulation of dysfunctional mitochondria and altered sarcoplasmic reticulum, leading to apoptosis and degeneration of muscle fibers in collagen VI null mice (Grumati et al., 2011). Defective autophagy or excessive autophagy is detrimental for muscle health, and even may have a pathologic role in several forms of muscle diseases. For example, defective activation of autophagy machinery plays a key role in the pathogenesis of muscular dystrophies linked to collagen VI (Grumati et al., 2011). The role of exercise in attenuating autophagy to modulate cardiac hypertrophy has been studied by Willis et al. (2013). The carboxyl terminus of Hsp70-interacting protein (CHIP) is an ubiquitin ligase/co-chaperone critical for maintaining cardiac function. Mice lacking CHIP suffer decreased survival, enhanced myocardial injury, and increased arrhythmias following challenge with cardiac ischemia reperfusion injury (Willis et al., 2013). CHIP plays a role in chaperone-assisted selective autophagy that is associated with exercise-induced cardioprotection. CHIP also plays a role in inhibiting Akt signaling and autophagic flux in cardiomyocytes and intact heart (Willis et al., 2013). Exercise, in addition, can induce autophagy in the brain tissue, which in part mediates its beneficial effects on neurodegeneration and improves cognitive function (He et al., 2012a). It


OVERVIEW OF AUTOPHAGY

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has been reported that autophagy eliminates protein aggregates and damaged organelles in neurons (Komatsu et al., 2006). Exercise also improves neuronal synaptic plasticity, promotes adult neurogenesis, and delays the onset of neurodegenerative diseases (Cotman et al., 2007). Autophagy is also activated in response to ultraendurance exercise. Some information is available on the effect of ultraendurance exercise on the autophagy regulatory genes. Transcript levels of the autophagy-regulatory genes BNIP3 and BNIP31 are increased in human muscle after ultraendurance exercise (Jamart et al., 2011). BNIP3 is known to regulate mitochondrial integrity, autophagy, and cell survival (Tracy and Macleod, 2007). Ultraendurance exercise also increases the production of reactive oxygen species (ROS) in isolated mitochondria from human skeletal muscle (Sahlin et al., 2010). A brief comment on the advantage of having adequate sleep is in order. A novel function of sleep relevant to the removal of aberrant or excess proteins from the brain is suggested. It is known that sleep has many functions, including enhancing the immune system and consolidating memories. Recently, it was proposed that the core function of sleep is to clean the brain from metabolic waste products. This suggestion is based on the evidence that when mice sleep, a network of transport channels expand by 60%, increasing the flow of cerebral spinal fluid. This surge of fluid clears away metabolic waste products such as β amyloid proteins that can plaster neurons with plaques that are associated with AD (“To Sleep, Perchance to Clean,” Science, 2013). It is possible that perpetual deprivation of sleep might play a role in the development of neurological diseases. It is also known that sleep deprivation results in lower antibody production, which, in turn, results in a lower immune response; both innate and adaptive immunity are diminished (Majde and Krueger, 2005). Adequate sleep, in contrast, supports the formation of long-lasting immune memory through the initiation of TH-1 immune response (Besedovsky et al., 2012). Also, it seems that lack of sleep encourages people to over-eat. Sleep restriction boosts the endocannabinoid 2-arachidonoylglycerol (2-AG) signal, rising above normal levels, which triggers the desire to eat. The role of diet in health is explained below. Diet plays a central role in maintaining health throughout life. A reduction of food and/ or calorie intake without malnutrition is associated with the prolongation of health. Health means the ability of a system to maintain or return to homeostasis in response to challenges. Dietary factors can slowdown age-related diseases such as cardiovascular diseases, Type 2 diabetes mellitus, neurodegenerative diseases, and cancer. Regarding the role of healthy diet, a caloric restriction (CR) induces autophagy that counteracts the development of agerelated diseases and aging itself. On the other hand, autophagy is inhibited by high glucose and insulin-induced phosphoinositide 3-kinase (PI3K) signaling via Akt and mTOR. Based on its fundamental roles in the prevention and therapy of disease processes, autophagy has emerged as a potential target for disease. A brief comment on the use of vitamins in the context of healthy food seems relevant. Intake of supplements is beneficial only if a person is deficient in a nutrient, and a strong medically-based cause has been determined. Generally, people should be able to obtain all the vitamins and minerals needed from a healthy, balanced diet. This is true for people living in the industrially advanced countries. Unfortunately, some people routinely take supplements as an “insurance policy” against diseases and to promote wellness. Commercials advertising “one-a-day, multi-vitamins,” unfortunately, persuade some persons to become addictive to vitamins. On the contrary, an excess intake of certain supplements (e.g., iron) is


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linked to early death. However, elderly people might need certain supplements such as vitamin D. It is concluded that intake of excess supplements is harmful, especially with time. Discipline is required to attain this goal. Unfortunately, inevitable death rules our lives. It is known that there is “no birth in the absence of death and vice versa”; a group of abnormal cells plays a part in this process. Safe disposal of cellular debris is crucial to keep us alive and healthy. Our body uses autophagy and apoptosis as clearing mechanisms to eliminate malfunctioning, aged, damaged, excessive and/or pathogen-infected cell debris that might otherwise be harmful/auto immunogenic. Damaged macromolecules and cell organelles can accumulate because of reduced degradation, reduced antioxidant capacity, or increased production of ROS. However, if such clearing process becomes uncontrollable, it can, instead, be deleterious. For example, deficits in protein clearance in the brain cells because of dysfunctional autophagy may lead to dementia. Autophagy can also promote cell degradation and/or lead to death through excessive self-digestion and degradation of essential cellular constituents. Humans and other mammals with long life spans, unfortunately, have to face the problem of getting old and the accumulation of somatic mutations over time. Although most of the mutations are benign and only some lead to disease, there are too many of them. Cancer is one of these major diseases, which is caused by a combination of somatic, genetic alterations in a single cell, followed by uncontrolled cell growth and proliferation. Even a single germline deletion of or mutation in a tumor suppressor gene (e.g., p53) predisposes an individual to cancer. It is apparent that nature tries to ensure the longevity of the individual by providing tumor suppressor genes and other protective machineries. The autophagy-related ATG gene Beclin 1 is a tumor suppressor gene and the autophagy process is one of these machineries that plays an important role in influencing the aging process. Autophagy research is in an explosive phase, driven by a relatively new awareness of the enormously significant role it plays in health and disease, including cancer, other pathologies, inflammation, immunity, infection, and aging process. The term autophagy (auto phagin from Greek meaning self-eating) refers to a phenomenon in which cytoplasmic components are delivered to the lysosomes for bulk or selective degradation under distinct intracellular and extracellular milieu of the lysosomes. This term was first coined by de Duve over 46 years ago (Deter and de Duve, 1967) based on the observed degradation of mitochondria and other intracellular structures within lysosomes of rat liver perfused with the pancreatic hormone, glucagon. During the last two decades an astonishing advance has been made in the understanding of the molecular mechanisms involved in the degradation of intracellular proteins in yeast vacuoles and the lysosomal compartment in mammalian cells. Advances in genome-scale approaches and computational tools have presented opportunities to explore the broader context in which autophagy is regulated at the systems level. A simplified definition of autophagy is that it is an exceedingly complex process that degrades modified, superfluous (surplus), or damaged cellular macromolecules and whole organelles using hydrolytic enzymes in the lysosomes. Autophagy can be defined in more detail as a regulated process of degradation and recycling of cellular constituents and organelles turnover, resulting in the bioenergetic management of starvation. This definition, however, still represents only some of the numerous roles played by the autophagic machinery in mammals; most of the autophagic functions are listed later in this chapter.


Specific Functions of Autophagy (A Summary)

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Autophagy plays a constitutive and basally active role in the quality control of proteins and organelles, and is associated with cell survival. Stress-responsive autophagy can enable adaptation and promote cell survival, whereas, in certain models, autophagy has also been associated with cell death, representing either a failed attempt at survival or as shown to be a mechanism that supports cell and tissue degradation. Autophagy prevents the accumulation of random molecular damage in long-lived structures, particularly mitochondria, and more generally provides a means to reallocate cellular resources from one biochemical pathway to another. Consequently, it is upregulated in conditions where a cell is responding to stress signals, such as starvation, oxidative stress, and exercise-induced adaptation. The balance between protein and lipid biosynthesis, their eventual degradation, and resynthesis are critical components of cellular health. Degradation and recycling of macromolecules via autophagy provides a source of building blocks (amino acids, fatty acids, sugars) that allow temporal adaptation of cells to adverse conditions. In addition to recycling, autophagy is required for the degradation of damaged or toxic material that can be generated as a result of ROS accumulation during oxidative stress. The mitochondrial electron transport chain and the peroxisomes are primary sources of ROS production in most eukaryotes.

SPECIFIC FUNCTIONS OF AUTOPHAGY (A SUMMARY) Autophagy plays a direct or indirect role in health and disease, including embryogenesis, postnatal and organogenesis development, tissue homeostasis (protein and cell organelle turnover), mitochondrial quality control, protein quality control, cellular homeostasis, protection of cells from stresses, survival response to nutrient deprivation, adaptive responses to starvation, cellular survival or physiological cell death during development, involvement in cell death upon treatment with chemotherapy and radiotherapy, tissue remodeling during differentiation and development, including regulation of number of cells and cell size, endocytosed gap junctions, villous trophoblasts, cellular house-cleaning, protein, glucose, and lipid metabolism, supply of energy, antiaging, human malignancy, tumorigenesis, tumor maintenance, inflammation, cancer (pro and anti), cancer metastasis, ovarian cancer, nasopharyngeal carcinoma, melanoma, colon cancer, neutrophil differentiation of acute promyelocytic leukemia, lysosomal storage diseases, metabolic disorders, osteoarthritis, cardiovascular diseases, alcoholic cardiomyopathy, steatosis in alcoholics (fatty degeneration of the heart), neurodegenerative diseases (Alzheimer’s, Parkinson’s, Huntington’s, amyotrophic lateral sclerosis, and prion disease), muscular dystrophy, macular degeneration, autosis, skeletal myopathy, atherosclerosis, diabetes, obesity, lipid degradation in the liver, alcoholic liver disease, pancreatitis, cellular quality control, protection of the genome, innate and adoptive immune responses to infection by microbial pathogens, defense against intracellular bacterial, parasitic, and viral infections, protection of intracellular pathogens, epileptogenesis, Pompe disease, nephropathy, reduction of liver damage during ischemiareperfusion, regression of the corpus luteum, protection of stem cells from apoptosis during stress, and cross talk with apoptosis, adaptation of neonates to starvation by inducing autophagy, prodegradation or antidegradation of pathogens, sequestration of damaged lysosomes, cellular signaling, maintenance of muscle mass, homeostatic maintenance of adult


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tissues, tissue remodeling, neuronal degeneration, survival from deprivation of nutrition and growth factors, prevention of malignant transformation, prevention of genomic instability and tumorigenesis, maintenance of nuclear and mitochondrial genomic integrity, dictating cell fate after genotoxic stress, regulation of cell fate after DNA damage, micronuclei degradation, cross talk between autophagy and apoptosis, degradation of excessive and dysfunctional cellular components, prevention or delaying the growth of transformed normal cells, association with apoptosis and mitochondrial change in pathogenesis, induction of osteogenesis, antigen presentation, chromatophagy, nucleophagy, depending on the cell/ tissue context: modulation of cell migration and membrane recycling, and other functions.

AUTOPHAGY PROCESS The simplified process of autophagy is summarized below. The formation of an autophagic isolated, crescent-shaped structure called phagophore is the beginning of this process. Beclin 1, serine/threonine protein kinase ULK1, autophagy-related LC3 proteins, and γ-aminobutyric acid receptor-associated proteins (GABARAPs) are key regulators of phagophore formation. Phagophore is transiently connected to and derived from phosphatidylinositol-3-phosphate (PtdIns3P)-positive domains of the endoplasmic reticulum (ER), which are known as omegasomes. Other cell structures participating in the phagophore formation include mitochondria, Golgi apparatus, and plasma membrane-derived endocytic organelles (Mizushima et al., 2011). The phagophore sequesters and captures the cytoplasmic cargo, followed by elongation and closure; at this stage, phagophore is a double membrane. This is simultaneously followed by the formation of autophagosomes (discussed elsewhere in this chapter) surrounded by a double membrane. Such autophagosomes mature into having a single membrane, fuse with phagophores, and receive from them the cargo, resulting in the formation of autolysosomes and beginning of cargo degradation by hydrolases at an acid pH.

AUTOPHAGY IN NORMAL MAMMALIAN CELLS Although autophagy mediates cell adaptation to a range of stress conditions, including starvation, this stress is not the problem that a normal cell of multicellular organism would face on a regular basis. The basal level of autophagy (the so-called basal or quality control autophagy) is found in most cells, and is required for the normal clearance of potentially deleterious protein aggregates that can cause cellular dysfunction. Thus, mammalian autophagy is primarily required for intracellular cleaning of misfolded proteins and damaged/old organelles. In the absence of such cleaning, neoplastic transformation is likely. As alluded above, starvation is uncommon in mammalian cells under normal nutritional conditions. Therefore, it is important to know the mechanism responsible for regulating autophagy under normal nutritional conditions. In mammalian cells, mTOR kinase, the target of rapamycin, mediates a major inhibitory signal that represses autophagy under nutrient-rich conditions. Calpain 1 keeps autophagy under a tight control by down regulating the levels of Atg12-Atg5 conjugate. Atg5 and Atg12-Atg5 conjugates are key signaling


Endoplasmic Reticulum

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molecules for increasing the levels of autophagy (Xia et al., 2010). It is also known that intracellular Ca2+ regulates autophagy. Inhibition of Ca2+ influx results in the induction of autophagy. Reduction in the intracellular Ca2+ prevents the cleavage of Atg5, which, in turn, increases the levels of full-length Atg5 and Atg12-Atg5 conjugate. The Atg12-Atg5 signaling molecule is regulated by calpain 1 in controlling the levels of autophagy in mammalian cells under nutrient-rich conditions. It is known that inhibition of calpains induces autophagy and reduces the accumulation of misfolded proteins. It is further known that increased levels of LC3II in fluspirilene-treated cells promote autophagy by increasing the levels of Atg5 and Atg12-Atg5 conjugates; fluspirilene is one of the autophagy inducers. Although autophagy is maintained at very low levels in normal mammalian cells, it can be rapidly induced within minutes upon starvation or invasion by intracellular pathogens.

ENDOPLASMIC RETICULUM All eukaryotic cells contain an ER, and its highly convoluted single membrane constitutes more than half of the total membrane system of the cell. Ribosomes are attached to the surface of the rough ER membranes, but ribosomes are also found free in the cytosol. These two types of ribosomes are the site of synthesis of different classes of proteins, with different functions. ER plays a central role in cell biosynthesis. It is a complex organelle in which secreted and membrane proteins are synthesized (assembled), modified, and folded. The synthesis of transmembrane proteins and lipids of the ER, Golgi complex, lysosomes, and plasma membrane begins in association with the ER membrane. Most of the lipids that constitute the membranes of mitochondria and peroxysomes are also contributed by the ER. In addition, all of the newly synthesized unfolded proteins are first delivered to the ER lumen for refolding before becoming part of the Golgi complex and lysosomes. Disulfide isomerase and chaperone Hsp70 proteins catalyze the refolding. The ER is also involved in biosynthesis of the extracellular matrix and of secreted proteins. Indeed, ER is the center of chaperone proteins that are responsible for correct folding of secreted proteins. In this system, lectinbinding proteins (calreticulin and calnexin) facilitate glycoprotein folding; glucose-regulated protein complex is also involved in this system (McLaughlin and Vandenbroeck, 2011). Another important function of ER, as indicated above, is in the biogenesis of autophagosomes by providing the site for omagasome formation and the source of membrane used. Double FYVE domain-containing protein 1 (DFCP1) is also located at ER and Golgi membranes instead of endosomes, and is involved in the formation of autophagosomes. This protein contains two FYVE domains, explaining its PI(3)P binding. Ave et al. (2008) have exploited the localization and movement of DFCP1 during amino acid starvation for identifying a PI(3)P-enriched compartment dynamically connected to the ER. It was further demonstrated that Pl(3)P compartment was formed near the Vps34-containing vesicles that provide a membrane platform for the accumulation of autophagosomal proteins, expansion of autophagosomal membranes, and fully formed autophagosomes. Eukaryotic cells are exposed to a large variety of cellular stresses, including nutrient or growth factor deprivation, hypoxia, ROS, DNA damage, protein accumulation, and damaged cell organelles. Such exposed cells must adapt to functions in parameters such as


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temperature, ultraviolet light, ion concentrations, pH, oxygen tension, redox potentials, cytokines, and neurotransmitters (Kroemer et al., 2010). Most of the folding and post-translational processing of membrane-bound proteins and secreted proteins occur in the ER under an array of chaperone systems such as glycosidases Ca2+-dependent chaperones, and members of the protein disulfide isomerase family (Deegan et al., 2013). These chaperones are responsible for the correct folding of proteins under normal physiological conditions. When this finely balanced unique environmental condition is disrupted, the protein folding machinery of the ER becomes less efficient or nonfunctional, resulting in the ER stress. It has been reported that human hepatitis B virus may induce autophagy through the induction of ER stress (or through the HBx protein) enhancing its replication (Tian et al., 2015). The involvement of ER stress in Crohn’s disease has also been reported (Bringer et al., 2014). ER stress, in addition, is known to induce autophagy-mediated cell death, and DAPK (deathassociated protein kinase) is an essential mediator of this process (Kabi and McDonald, 2014). The ER stress and Unfolded protein response (UPR) are intimately intertwined. The ER stress is capable of activating autophagy, a function that is conserved from yeast to mammals (Fritz et al., 2013). It is known that eukaryotic initiation factor 2 (eIF2) induces autophagosome formation under stress conditions (Ogata et al., 2006). Thus, autophagy complements ER-associated degradation (ERAD) induced during unfolded protein response (UPR) (Fujita et al., 2007). It is now accepted that when cell is subjected to stress, depending on the amount of stress, the autophagy can induce either a cell survival signal or a death signal. If the stress is mild, it generates an adaptive response to survival against the stress, and autophagy results in survival signal by activating several genes and transcription factors, which alter the stress-induced death signal into a survival signal (Das, 2011). This change leads to the production of antiapoptotic (antideath) proteins. In contrast, if the stress is excessive, the adaptive response fails, and the cell dies as a result of the introduction of apoptotic signals.

ER Stress The ER stress results when unfavorable physiological or pathological conditions cripple the ER protein folding machinery to correctly fold nascent proteins. It occurs upon the accumulation of misfolded or unfolded proteins in the ER. As a result, ER plays a pivotal role in the development of pathology of many neurodegenerative disorders, including Alzheimer’s, Parkinson’s, and prion (Creutzfeldt Jacob’s disease) and amyotrophic lateral sclerosis. DFCP1 during amino acid starvation for identifying a P1(3)P-enriched compartment is dynamically connected to the ER. It was further demonstrated that this compartment was formed near the Hps34-containing vesicles that provide a membrane platform for the accumulation of autophagosomal proteins, expansion of autophagosomal membranes, and fully formed autophagosomes. ER is also involved in the degradation (removal) of misfolded proteins. For example, Cortes et al. (2013) have demonstrated the intracellular trafficking and degradation of newly synthesized misfolded/aggregated mutant prion protein (PrP) assisted by ER.


Major Types of Autophagies

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The initial and rapid response of cells to the ER stress is the activation of a set of prosurvival signaling pathways called the UPR, which is a catabolic process resulting in autophagy and cell death (Doyle et al., 2011; Gorman et al., 2012). The primary function of UPR is to sustain cell survival. The UPR regulates protein folding capacity of the ER by sensing the presence of unfolded proteins in the ER lumen, transmitting the information to the cell nucleus, where it drives a transcriptional program focused to reestablish homeostasis (Bernales et al., 2006b). In mammals, the six major ER sensors are IRE1 (inositol requiring 1), IERN1 (ER-to-nucleus signal: img 1), PKR-like ER kinase (PERK) (double-stranded RNA-activated protein kinase (PKR)-like kinase), PEK (pancreatic eukaryotic initiation factor 2α kinase), EIF2AK3, and ATF6 (activating transcription factor 6) (Ron and Walter, 2007). IRE1 and PERK are type 1 transmembrane proteins with protein kinase activity, while ATF6 is a type II transmembrane protein encoding a transcription factor (Schröder and Kaufman, 2005). Bernales et al. (2006a,b) demonstrated that the ER volume increased under UPR-inducing conditions in the yeast. The ER expansion was accompanied by the formation of autophagosomes that packed membranes derived from the UPR-expanded ER. The ER-specific autophagy utilizes autophagy genes. Such genes are activated by the UPR and are essential for the survival of cells exposed to ER stress. Such selective ER sequestration maintains a steady-state level of ER abundance during continuously accumulating unfolded proteins (Bernales et al., 2006a). The UPR also blocks protein synthesis and activates mechanisms that prepare the cell to cope with the aggregated unfolded proteins. One of such mechanisms involves the enhancement of the protein folding capacity of the ER by increasing the expression of ER chaperone proteins and upregulating the degradation of misfolded proteins (Doyle et al., 2011). However, prolonged or excess ER stress may activate apoptosis. Proapoptotic factors (including cytochrome c) are released by the UPR by opening the mitochondrial permeability transmembrane pores. In conjunction with apoptotic protease activating factor 1 (Apaf-1), procaspase 9, and cytochrome c form the apoptosome (Olson and Kornbluth, 2001). The apoptosome is a complex consisting of adaptor proteins that mediate the activation of initiator caspases at the onset of apoptosis. In conclusion, the development of the UPR protects cells from the deleterious effects of the ER stress. When the ER stress is not removed, it can be lethal or harmful to cells causing neurodegenerative and cardiovascular diseases, cancer, or diabetes. Overexpression of Bcl-2 also protects cells from ER stress-induced death. Conditions that induce ER stress also induce autophagy. It is well-established that autophagy constitutes a major protective mechanism that allows cells to survive in response to multiple stressors, and it helps organisms to defend against degenerative, inflammatory, infectious, and neoplastic disorders. It needs to be noted that ER stress itself is capable of activating autophagy, while impaired autophagy can promote ER stress.

MAJOR TYPES OF AUTOPHAGIES Based on the type of cargo delivery, there are three types of autophagy systems in mammals: macroautophagy (autophagy), microautophagy, and chaperone-mediated autophagy (CMA), each of which is discussed here. Although significant advances (some of which


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are discussed here) have been made in our understanding of different types of autophagies, many unanswered questions remain. A further understanding of the exact functions of the three types of autophagy is necessary before we can manipulate these pathways to treat human diseases.

Macroautophagy (Autophagy) Whole regions of the cytosol are sequestered and delivered to lysosomes for degradation. Cargo sequestration occurs during formation of the autophagosome, a double membrane vesicle that forms through the elongation and sealing of a de novo generated membrane (Ohsumi and Mizushima, 2004). This limiting membrane originates from a tightly controlled series of interactions between more than 10 different proteins, which resemble the conjugation steps that mediate protein ubiquitinization (Cuervo, 2009). Formation of the limiting membrane also requires the interaction between a protein and a specific lipid molecule, regulated by conjugating enzymes.

Microautophagy Microautophagy is the direct uptake of soluble or particulate cellular constituents into lysosomes. It translocates cytoplasmic substances into the lysosomes for degradation via direct invagination, protrusion, or septation of the lysosomal limiting membrane. In other words, microautophagy involves direct invagination and fusion of the vacuolar/lysosomal membrane under nutrient limitation. The limiting/sequestering membrane is the lysosomal membrane, which invaginates to form tubules that pinch off into the lysosomal lumen. Microautophagy of soluble components, as in macroautophagy (autophagy), is induced by nitrogen starvation and rapamycin. Microautophagy is controlled by the TOR and EGO signaling complexes, resulting in direct uptake and degradation of the vacuolar boundary membrane (Uttenweiler et al., 2007). Hence, this process could compensate for the enormous influx of membrane caused by autophagy. It seems that microautophagy is required for the maintenance of organelle size and membrane composition rather than for cell survival under nutrient restriction. Uttenweiler et al. (2007) have identified the vacuolar transporter chaperone, VTC complex, required for microautophagy. This complex is present on the ER and vacuoles and at the cell periphery. Deletion of the VTC complex blocks micrautophagic uptake into vacuoles.

Chaperone-Mediated Autophagy CMA is a generalized form of autophagy present in almost all cell and tissue types. It has been characterized in higher eukaryotes but not in yeast. Because of the particular characteristics of this type of delivery explained below, only soluble proteins, but not whole organelles, can be degraded through CMA (Cuervo, 2009). CMA is dependent on the constitutively expressed heat shock cognate 70 (hsc70), shares 80% homology with the heat shock protein 70 (Hsp70), and identifies peptide sequences of cytoplasmic substrates; thus, being more selective than autophagy in its degradation (Hoffman et al., 2012). CMA serves to balance dysregulated energy, and is maximally activated by nutrient/metabolic and


Autophagosome Formation

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oxidative/nitrosative stresses. Cross talk between CMA and autophagy is likely. CMA differs from the other two types of autophagies with respect to the mechanism for cargo selection and delivery to the lysosomal lumen for degradation. In other words, CMA is involved in the delivery of cargo, which does not require the formation of intermediate vesicles, membrane fusion, or membrane deformity of any type. Instead, the substrates are translocated from the cytosol directly into the lysosomal lumen across the membrane in a process mediated by a translocation protein complex that requires the substrate unfolding. A chaperone protein binds first to its cytosolic target substrate, followed by a receptor on the lysosomal membrane at the site of protein unfolding. This protein is subsequently translocated into the lysosome for its degradation. In this system the substrate proteins are selectively targeted one-by-one to the lysosomes, and are then translocated across the lysosomal membrane. This selectivity and direct lysosomal translocation have thus become trademarks of CMA. All CMA substrate proteins are soluble cystolic proteins. An essential requirement for a protein to become a CMA substrate is the presence of a pentapeptide motif biochemically related to KFERQ in its amino acid sequence (Dice, 1990). The motif present in 30% of the proteins in the cytosol is recognized by a cytosolic chaperone, the heat shock cognate protein of 73 kDa (cyt-hsc70). The interaction with chaperone, modulated by the hsc70 cochaperones, targets the substrate to the lysosomal membrane, where it interacts with the lysosomal membrane protein (LAMP) type 2a (Cuervo and Dice, 1996). During CMA, proteins are directly imported into lysosomes via the LAMP-2a transporter assisted by the cytosolic and lysosomal HSC70 chaperone that recognizes the KFERG-like motif. Substrates of CMA carry signal peptides for sorting into lysosomes, similar to other protein-transport mechanisms across membranes. Substrates are required to be unfolded before translocation into the lysosomal lumen. Several cytosolic chaperones associated with the lysosomal membrane have been proposed, which assist in the unfolding (Agarraberes and Dice, 2001). Translocation of the substrate requires the presence of a variant of hsc70, lys-hsc70, in the lysosomal lumen. This is followed by the rapid proteolysis of the substrate by residual lysosomal proteases (half-life of 5–10 min in the lysosomal lumen).

AUTOPHAGOSOME FORMATION Autophagy is a highly complex process consisting of sequential steps of induction of autophagy, formation of autophagosome precursor, formation of autophagosome, fusion between autophagosome and lysosome, degradation of cargo contents, efflux transportation of degraded products to the cytoplasm, and lysosome reformation. In mammalian cells autophagosome formation begins with a nucleation step, where isolation membranes of varied origins form phagophores, which then expand and fuse forming completed double-membrane vesicle called autophagosome (Luo and Rubinsztein, 2010). Autophagosomes are formed at random sites in the cytoplasm. They move along microtubules in a dynein-dependent fashion toward the microtubule-organizing center where they encounter lysosomes. After fusion with lysosomes the cargo is degraded with hydrolases, followed by the reformation of lysosomes primarily by the Golgi complex.


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The isolation membranes may be generated from multiple sources that include ER, Golgi complex, outer mitochondrial membrane; however, the ER source is more feasible because it along with its ribosomes is involved in protein synthesis. As indicated above, various intracellular membranes are the source of formation of mature autophagosomes. Recent studies, using various methods, including immunocytochemistry, immuno-gold electron microscopy, and live cell imaging, indicate that plasma membrane contributes to the early autophagosomal precursor structures (Ravikumar et al., 2011). This phenomenon is dependent on the association of Atg16L1-positive vesicles with the plasma membrane via Atg16L1-AP2/clathrin heavy chain interactions. Subsequent scission of the Atg16L1/clathrin/AP2-associated structure leads to the formation of early endosomal-like intermediates (Ravikumar et al., 2011). This is an important step toward the liberation and maturation of these Atg16L1 vesicles that form autophagosomes. These autophagosome precursor membranes may precede the formation of phagophores. The presence of many Atg proteins near the ER also suggests that ER plays an important role as a membrane source for autophagosome formation. The formation of isolation membrane is initiated by class III PI3K (PI3KCIII)/Beclin 1–containing complexes. The elongation of the isolation membrane involves two ubiquitin-like conjugation systems. In one of them, Atg12 associates with Atg5 to form Atg12-Atg5-Atg16L1 molecular complexes that bind the outer membrane of the isolation membrane. In the second, LC3 is conjugated to phosphatidylethanolamine (PE) to generate a lipidated LC3-II form, which is integrated in both the outer and inner membranes of the autophagosome (Fujita et al., 2008). Recently, it was reported that human ATG2 homologues ATG2A and ATGB are also essential for autophagosome formation, presumably at a late stage (Velikkakath et al., 2012). Autophagosome membrane formation requires critical autophagy proteins (Atgs) along with the insertion of lipidated microtubule-associated light chain 3 (LC3) or GABARAP subfamily members. Various components in the autophagosomal compartment can be recognized by the presence of specific autophagy molecules. Atg16L1 and Atg5 are mainly present in the phagophore, while LC3 labels isolation membranes, matured autophagosomes, and autolysosomes (Gao et al., 2010). This evidence suggests that different Atg molecules participate in autophagosome biogenesis at various stages. Substrate selectivity can be conferred by interactions between LC3 and specific cargo receptors, including sequestosome-1 (SQSTM1 p62) and a neighbor of BRCA1 (NBR1). During this process of autophagy, both lipidated LC3 (LC-3-11) and the cargo receptors are degraded (Hocking et al., 2012). In yeast, Atg5-Atg12/Atg16 complex is essential for autophagosome formation (Romanov et al., 2012). This complex directly binds membranes. Membrane binding is mediated by Atg5, inhibited by Atg12, and activated by Atg16. All components of this complex are required for efficient promotion of Atg8 conjugation to PE. However, this complex is able to tether (fasten) membranes independently of Atg8.

AUTOPHAGIC FLUX Autophagic flux is a measure of the autophagic degradation activity. Autophagy functions at basal levels to turn over damaged, misfolded, aged, and excess macromolecules, including proteins, and is the only process that turns over organelles. This process,


Autophagic Lysosome Reformation

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therefore, is critically important for preserving cellular integrity and viability and health. Autophagy is also highly adaptable, and the type of cargo and its rate of disposition can be changed to accomplish necessary cellular responses to intracellular and environmental signals (cues), disease states, and a spectrum of pharmaceutical drugs (Baudot et al., 2015). In contrast to the beneficial effects of autophagy influx, several studies indicate that autophagy is upregulated and required for the survival of certain types of tumor cells, especially those in a hypoxic tumor regions (White, 2012). Activated Ras requires autophagy to maintain oxidative metabolism and tumorigenesis (Guo et al., 2011). Pancreatic cancer requires autophagy for tumor growth (Yang et al., 2011). Lock et al. (2014) indicate that autophagy-dependent production of secreted factors facilitate oncogenic Ras-driven invasion. These and other studies indicate that autophagy has a context-dependent role in cancer. In order to be able to manipulate autophagy for therapy, it is necessary to determine the rate of autophagic flux in normal versus diseased cells. Autophagy can be promoted, for example, to facilitate the clearance of aggregated proteins associated with neurodegenerative diseases. A number of methods have been suggested for assessing autophagic flux, which infer whether or not such a flux is occurring (Klionsky et al., 2012). Two recently developed methods are presented. Loos et al. (2014) have developed a method for defining and measuring autophagosome flux at the single cell level. This method is based on the well-established metabolic control analysis (Kacser et al., 1995). The method proposed by Loos et al. (2014) distinguishes between the pathways along which cellular materials flow and measures the quantitative flow of the cargo being degraded. This method can determine that autophagic flux is a multistep pathway with each step characterized by a particular rate. The second approach is an assay to measure changes in endogenous cargo degradation by engineering cells to en masse degrade mitochondria (Baudot et al., 2015). This assay differs from other available methods in that the enhanced-mitophagy approach can be used to measure differences in the rate of autophagy between different cells or in response to agents that promote or inhibit autophagic flux. In order to be able to manipulate autophagy, it is necessary to determine the rate of autophagic flux in normal versus diseased cells to manipulate autophagy for therapy.

AUTOPHAGIC LYSOSOME REFORMATION Following degradation of engulfed substrates with lysosomal hydrolytic enzymes and release of the resulting molecules (amino acids, fatty acids, monosaccharides, nucleotides), autophagic lysosome reformation (ALR) occurs. Although a great deal is known regarding the molecular mechanisms involved in the formation of autophagosomes and autolysosomes, the available information on the post-degradation events, including the ALR is inadequate. The importance of such information becomes apparent considering that one autophagosome can fuse with multiple lysosomes. Thus, post-degradation of substrates might result in the depletion of free lysosomes within a cell unless free lysosomes are rapidly reformed. A cellular mechanism is required for maintaining lysosome homeostasis during and after autophagy.


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Some information is available at the molecular level regarding the process of ALR. The ALR process can be divided in six steps (Chen and Yu, 2012): phospholipid conversion, cargo sorting, autophagosomal membrane budding, tubule extension, budding and fusion of vesicles, and protolysosome maturation. Initially, LAMP1-positive tubular structures extend from autolysosomes, which are empty-looking without detectable luminal contents from autolysosomes. Lysosomal membrane proteins (LAMP1, LAMP2) only are located on these tubules, but autophagosomal membrane proteins (LC3) are absent. The role of mTOR is also relevant in the ALR. It has been found that the starvationinduced autophagy process is transient. During starvation, intracellular mTOR is inhibited before autophagy can occur, but it is reactivated after prolonged starvation, and the timing of this reactivation is correlated with the initiation of ALR and termination of autophagy (Chen and Yu, 2012). Thus, mTOR reactivation is required for ALR. ALR is blocked when mTOR is inhibited, and mTOR reactivation is linked to lysosomal degradation. The lysosomal efflux transporter spinster is also required to trigger ALR (Rong et al., 2011); these transporters are LAMPs that export lysosomal degradation products. Sugar transporter activity of spinster is essential for ALR. Inhibition of spinster results in the accumulation of a large amount of undigested cytosol in enlarged autolysosomes seen in the transmission electron microscope, as a result of over-acidification of autolysosomes (Rong et al., 2011). Clathrin is also essential for ALR. It is known that clathrin proteins play an important role in vesicular trafficking (Brodsky, 1988). Clathrin mediates budding in various membrane systems. A clathrin-PI (4, 5) P2-centered pathway regulates ALR. This protein is present on autolysosomes, with exclusive enrichment on vesicle buds. Clathrin itself cannot directly anchor to membranes; instead, various adapter proteins (AP2) link clathrin to membranes. Additional studies are needed to fully understand the terminal stage of autophagy and how this process ends in the reformation of free lysosomes.

AUTOPHAGY AS A DOUBLE-EDGED SWORD Autophagy can inhibit a disease or promote a disease depending on the context. Thus, autophagy function can be enhanced to improve the treatment of a specific disease; alternatively, autophagy activity can be inhibited to achieve an effective treatment of a disease. Between these two options, the former has been reported in a vast majority of cases. Because the former option is discussed elsewhere in this chapter (role of autophagy in the defense of host cells infected with bacteria or viruses), the latter role of autophagy is reviewed here. It needs to be noted that different tumor cells react differently when autophagy is inhibited (Thorburn, 2014). A number of Phase I and Phase II clinical trials of autophagy inhibition in cancer patients have been and are being carried out. A few examples suffice. Levy et al. (2014) have reported that autophagy inhibition improves chemosensitivity in BRAF brain tumors. Maycotte et al. (2014) have also reported that autophagy inhibition can be efficacious against breast cancer. Phase II and pharmacodynamic study of autophagy inhibition using hydroxychloroquine in patients with metastatic pancreatic adenocarcinoma has been carried out, which was good for patients (Wolpin et al., 2014). Vogl et al. (2014) carried out combined autophagy and proteasome inhibition using hydroxychloroquine


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and bortezomib in patients with relapsed/refractory myeloma showing good results for patients. Undesirable effect of the presence of autophagy was reported by Yang et al. (2014b). They reported that the presence of autophagy is critical for growth and progression of pancreatic tumors with p53 alterations. Recent studies indicate that autophagy has opposing roles in cancer initiation and in established tumors. It is known that certain types of cancer (e.g., lung, pancreatic, and prostate) show a high prevalence of activating mutations in Ras and poor prognosis. It has been reported that pancreatic cancer has distinct dependence on autophagy in that pancreatic primary cancer tumors show elevated basal autophagy (Yang et al., 2011). Autophagy inhibitors such as chloroquine and its derivatives can be used for the treatment of pancreatic cancer patients. A series of relatively recent studies indicate that certain types of aggressive cancers show “autophagy addiction.” For example, autophagy is critically involved in malignant transformation by oncogenic K-Ras, and shows that ROS-mediated JNK activation plays a critical role in autophagy induction through upregulation of ATG5 and ATG7 (Kim et al., 2011). Mancias and Kimmelman (2011) have suggested that the survival of certain cancer cells, especially those driven by the K-Ras oncogene, also depends on the elevated levels of autophagy even in the absence of external stresses. Lock et al. (2011) also indicate that autophagy promotes Ras-driven tumor growth in specific metabolic contexts. It means that in the context of a potent oncogene (mutationally active Ras), autophagy promotes adhesion-independent transformation. Expression of K-Ras upregulates basal autophagy, which is required for tumor cell survival in starvation and tumorigeneses (Guo et al., 2011). As mitochondria sustain viability of Ras-expressing cells in starvation, autophagy is required to maintain the pool of functional mitochondria necessary to support growth of Ras-driven tumors (Guo et al., 2011). Human cells bearing activating Ras mutations have high levels of basal autophagy. Thus, targeting autophagy and mitochondrial metabolism are important approaches to treat these aggressive cancers (Guo et al., 2011).

PROTEIN SYNTHESIS It is known that autophagy plays a key role in the degradation of aberrant proteins. It is also known that if such proteins are not correctly refolded or degraded, they tend to accumulate, resulting in neurodegenerative and other diseases. Misfolded proteins result from mutations, for incomplete translation gives rise to defective ribosomal products. The delivery of misfolded proteins to lysosomes for their degradation by autophagy requires the function of several protein complexes and pathways, including mTORC1 complex, ULK1/ Atgl complex, LC3 conjugation pathway, and phosphatidylinositol 3-kinase (PI3K) class III/ VPS34 complex (Wani et al., 2015). It is also known that autophagic proteins and other proteins are subjected to regulatory posttranslational modifications. Proteins are slowly biosynthesized on the ribosome, and most of them do not begin to fold during synthesis and tend to form aggregates because of hydrophobic interactions (Fig. 1.1). Phosphorylation is the most important posttranslational modification in the autophagy process, followed by ubiquitination and acetylation


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FIGURE 1.1 The main driving force responsible for the formation of protein structure. The diagram on the lefthand side shows hydrophobic amino acids (black spheres) exposed to the external space, while the diagram on the right-hand side shows hydrophobic amino acids buried inside, shielded from the solvent. When the hydrophobic amino acids are exposed to high temperatures, high concentration of solutes, and chemical denaturants, proteins may not fold into their biochemically functional form or may unfold. Under certain conditions, chaperones assist proteins both in proper folding and in remaining folded. Chaperones may also unfold misfolded proteins and provide them with a second opportunity to refold properly.

(Wani et al., 2015). Phosphorylation induces changes in protein configuration by inserting a phosphate group onto serine, threonine, and tyrosine amino acids, resulting in the activation of autophagy and autophagosome formation, which, in turn, depend on the direct phosphorylation of Atg9 by the Atg1 kinase (Papinski et al., 2014). It is known that most proteins contain modifiable serine, threonine, lysine, or cysteine residues in response to nutrient availability, growth factor deprivation, hypoxia, hyperoxia, and generation and propagation of reactive species (Wani et al., 2015). Based on this and other evidence, it is apparent that a better understanding of the synthesis of proteins, especially misfolded (incompletely) proteins, is needed to decipher the molecular mechanisms underlying protein accumulation, sequestration, and degradation. It is important to know the fundamental molecular mechanisms underlying the formation of normal and abnormal proteins for understanding the function or failure of function of both types of proteins. Indeed, in order to understand the necessity of the removal of unfolded, misfolded, incompletely folded, or aggregated proteins by autophagy or other mechanisms, knowledge of the formation of such proteins is needed. Information regarding the conformational modifications of proteins (glycoproteins) is a prerequisite to fully understand this necessity. The removal of aberrant proteins avoids invitation to some pathological conditions such as neurodegenerative diseases. This subject is discussed in detail below. The word protein is derived from the Greek word proteios, meaning first or foremost, reflecting the functional importance of this molecule. Proteins participate directly or


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indirectly in virtually every process in a cell. Most of the chemical reactions in and structural components of a cell are mediated or supplied by proteins. In other words, proteins have many kinds of functions: structural proteins, regulatory proteins, and catalytic proteins. In addition to generating these biological activities, protein molecules are coupled to many other biological processes, including trafficking. Proteins are constantly synthesized as cells grow, reproduce, and repair themselves. So, proteins must be replenished during the life of the cell, which is carried out by autophagy and other processes. Proteins are long polymers made out of 20 amino acids. A protein of an average size has 300 amino acid residues, and the possible combinatorial number of proteins made with 20 amino acids is enormous. Amino acids are added sequentially instead of randomly to form a correct polypeptide under normal physiological conditions. The polypeptide always begins at its N-terminus and not at its C-terminus. A polypeptide may have a length of ~150 nm. Polypeptides are encoded by genes in the DNA. All the information required for a protein molecule to fold into its three-dimensional conformation is contained in the amino acid sequence. The three-dimensional structure of a protein allows it to perform its function, to connect with reactive sites on other proteins and molecules within the cell. Amino acids possess side chains, and some of them are hydrophobic, while others are hydrophilic; some are positively charged, while others are negatively charged. In a properly folded protein molecule, hydrophobic amino acids are located inside the protein molecule, whereas hydrophilic amino acids are located on the surface of the protein (Fig. 1.1). In contrast, in a misfolded protein, hydrophobic amino acids are located on the surface of the molecule, inviting chaperones to help correctly refold misfolded or partly folded proteins. Knowledge of the number of protein domains, which show little or no ordered structure under physiological conditions, has been increasing exponentially during the last two decades. Natively unfolded proteins lack ordered structure under conditions of neutral pH in vitro. These proteins are specifically located within a unique region of charge hydrophobicity phase space, and a combination of low overall hydrophobicity and large (high) net charge represent a unique structural feature of natively unfolded proteins (Uversky et al., 2000). Maintaining quality control over protein structure and function depends on molecular chaperones and proteases, both of which can recognize hydrophobic regions exposed on unfolded polypeptides (Wickner et al., 1999). Molecular chaperone proteins and the ubiquitin-proteasome degradation pathway protect eukaryotic cells against buildup of misfolded proteins; the former assist folding of newly translated and stress-denatured proteins (Hartl and Hayer-Hartl, 2009). Nevertheless, some misfolded polypeptides are not folded correctly under any circumstance (Zhang and Qian, 2011). Cellular proteins can be correctly folded (native state), misfolded, unfolded, incompletely folded, or aggregated. Fig. 1.2 shows schematic configurations of typical polypeptides, misfolded, aggregated protein molecules, and three-dimensionally folded, normal protein. The correct native interactions are more favorable than the incorrect nonnative ones. However, even the most carefully designed polypeptide may misfold, and find itself in a nonnative state where it might be at least transiently stable (Dobson, 2014). Only correctly folded proteins have long-term stability in a crowded biological environment to be able to interact selectively with their natural partners that include DNA, RNA, other proteins or peptides, and membranes. Thus, failure of proteins to fold correctly or to remain incorrectly folded


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FIGURE 1.2 (A) Schematic representation of protein folding. (B) X-ray crystallographic characterization of a three-dimensionally folded maltose-binding protein.

results in a wide variety of pathological conditions, including neurodegenerative diseases. In addition to the mechanism underlying the formation of aberrant proteins already discussed earlier in this chapter, the aging process is accompanied by mutations and thermodynamics, which conspire against us, resulting in the misfolding or incomplete folding of proteins (Renaud, 2010). Proper protein folding in the ER lumen is associated with the formation of disulfide bonds that are covalent linkages between two sulfhydryl groups in the two adjacent cysteine side chains. These bonds help to reinforce the conformation of the protein, stabilizing its structure. The presence of ATP and CA2+ concentration results in the minimization of protein folding capacity of the ER (Gorman et al., 2012). Consequently, unfolded proteins accumulate in the ER, causing ER stress (see later). However, the development of the UPR protects the cells from the deleterious effects of the ER stress. As mentioned above, formation of disulfide bonds is essential for the proper folding of proteins. In eukaryotic cells, disulfide bonds are confined to proteins synthesized in the


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ER. The reducing environment of the cytosol is not conducive to the formation of disulfide bonds, and thus they are formed in the ER. The ER lumen contains the enzyme protein disulfide isomerase (PD1), which catalyzes the formation of disulfide bonds between cysteine residues. Cysteine residues in their active site help to catalyze this reaction. This process precedes the completion of synthesis of newly forming polypeptides. As expected, PD1 becomes reduced in this process and needs to be reoxidized to be able to participate in another round of oxidation. This reaction depends on the ER protein oxidase 1 (Ero1), which contains flavin adenine dinucleotide (FAD) as a prosthetic group. Ero1 also contains a disulfide bond that is used to regenerate oxidized PD1. Ero1 itself is oxidized by molecular oxygen. In addition to forming disulfide bonds, PD1 can catalyze rearrangement of disulfide bonds, facilitating the enzyme to correct any inappropriate disulfide bonds that may have been formed as a protein folds. In this case, reduced PD1 forms a disulfide bond with the protein. The role of water molecules has been suggested to influence protein folding, instead of tumbling among themselves. Water molecules in the cell form teeming, shifting shells around ions, or sleeves around biomolecular chains. Water molecules may erect invisible, stability-enhancing scaffolds. Intracellular water molecules may assist biomolecules in their search for binding partners. Water molecules may form hydration funnels surrounding the binding pockets of proteins (Ruhr University Bochum). These funnels seem to facilitate biomolecules to recognize and bind to each other, such as correct protein folding. It does not seem to be uncommon that the structure and shape of a protein molecule undergo changes during its lifetime, depending upon its immediately required function. This phenomenon is fascinatingly shown by the HIV spike protein. A recent study by Munro and Mothes (2015) indicated that this protein rapidly shifts three different configurations, one of which is a closed state that is inaccessible to antibodies. Subsequently, it reverts to an open state to fuse and infect cells. Indeed, these transformations allow the virus to resist the immune defense system but also can infect cells. Apparently, an effective vaccine needs to be based on the closed state form of this viral protein. These authors obtained this information by using single molecule fluorescent resonance energy transfer microscopy at an atomic resolution. Finally, it is recognized that biological macromolecules are far from being rigid in their structure. Motion is also implicit in the normal function of molecules such as serum albumin and myoglobin (Austin et al., 1975). Binding sites for interacting proteins are frequently more mobile than the rest of the protein (Tainer et al., 1984). Cells carry out their various functions by synthesizing and degrading proteins on a regular basis. The routine degradation of abnormal (misfolded) and unwanted (excessive) proteins are accomplished primarily by the ubiquitin-proteasome system (UPS). The presence of unfolded proteins triggers the repair of these proteins by activating chaperone proteins. If this system fails, the cell activates the autophagy degradation mechanism to degrade these abnormal proteins. If this mechanism is not fully effective, misfolded proteins form aggregates (aggresomes). The formation of aggresomes may lead to autophagy. An aggresome is a protein complex containing abnormal proteins, chaperone proteins, proteasome components, mitochondrial components, and ubiquitinated proteins. The protein aggregates are transported along the microtubule network by motor protein dynein (Mi et al., 2009). These authors also reported that isothiocyanates (ITCs) (a small cancer chemopreventive molecule) can induce formation of aggresome-like structures.


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Methods A number of methodologies are available to study protein structure, unfolding, and refolding, three of them are summarized here. Uversky et al. (2000) have presented a method to predict whether a given protein assumes a defined fold or is intrinsically unfolded. This method is based on the average hydrophobicity of its amino acids and the value of its net charge. This simple procedure facilitates rapid prediction of whether a given amino acid sequence is disordered or not. These authors have presented a list of 91 known natively unfolded proteins and their major characteristics. The number of residues in these proteins ranges from 50 to 1827, and the net charge at pH 7.0 may range from +59 to −117. The second method consists of atomic force microscopy, which has become a prominent tool for studying the mechanical properties of proteins and protein interactions on a single-molecule level using chemicals or temperature as a denaturant (Borgia et al., 2008). The effect of force on thermodynamics and kinetics of single molecule reactions can be studied (Tinoco and Bustamante, 2002). Because many proteins fulfill mechanical functions or exert mechanical forces in their natural environment, AFM (atomic-force microscopy) facilitates targeting physiologically relevant questions. Another method in use is nuclear resonance microscopy that is particularly applicable to the study of unfolded and partly folded proteins. It provides unique structural insights into the events of protein folding process (Dyson and Wright, 1996, 2004, 2005). This approach has been instrumental in identifying and characterizing functional domains of these proteins.

Abnormal Proteins Intracellular proteins are subjected to continuous turnover through coordinated synthesis, degradation, and recycling of their component amino acids. Proteins can undergo degradation by the proteasome or by lysosomes. Proteins are degraded by macroautophagy, microautophagy, or CMA. CMA is especially efficient in the degradation of damaged or abnormal proteins, fulfilling its role in quality control. However, proteolytic systems in certain cases fail to adequately dispose of deleterious proteins, which results in protein aggregation and neuronal demise causing neurodegenerative diseases. The presence of unfolded or misfolded proteins in cells is not uncommon. It is estimated that ~30% of newly synthesized proteins are unfolded or incorrectly folded. The reason seems to be that protein folding is an exceedingly complex process because the transition from a linear sequence of amino acids to a correctly fully folded, three-dimensionally active protein requires at least favorable physiological environment and assistance from other biological molecules. The difference in the configuration of an unfolded polypeptide and a folded three-dimensional protein molecule is shown in Fig. 1.3. It is known, for example, that low molecular–weight chemical chaperones stabilize a protein as it folds into the proper structural form (Ferreon et al., 2012). In order to understand the damage (e.g., AD) caused by the accumulation of unfolded or misfolded proteins, it is important to identify and measure the quantity of such proteins. It is relevant to determine how much misfolded proteins actually cause cell damage or cell death. One method to visualize the interplay between fully folded and unfolded forms of proteins is by using a designed fluorescent tagged small molecule (folding probe)


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FIGURE 1.3 An unfolded polypeptide containing a linear chain of amino acids (left-hand side) and a threedimensional structure of the folded protein (native conformation) (right-hand side). Unfolded or misfolded proteins either remain inactive or become functionally toxic as accumulation of such proteins (e.g., amyloid fibrils) may cause neurodegenerative diseases, allergies, or type 2 diabetes (proteopathies). A protein molecule may fold spontaneously during or after biosynthesis and/or its folding depends on the solvent (water or lipid bilayer), the salt concentration, the pH, the temperature, cofactors, and molecular chaperones.

(Liu et al., 2014). This probe specifically binds to the folded, functional protein, but not to misfolded forms of protein. Thus, the quantification method can determine the comparative amount of folded protein versus misfolded protein in a cell. Autophagy in most cases is able to degrade misfolded proteins. Information to correct protein misfolding is available. In certain cases specific molecules (pharmacoperones) can correct protein misfolding in cells. An example of such therapeutic effect was reported by Janovick et al. (2013). They reported the rescue and expression of a misfolded G protein– coupled receptor (hormone), which contained a single amino acid change; a negatively charged glutamic acid was substituted by a positively charged lysine. This modification resulted in the misfolding and misrouting of the gonadal protein (GnRHR). By using 1N3 (a small molecule), they accomplished proper folding of the misfolded protein and restored normal gonadal function in the mutant mice. The normal function resulted from correct routing of the protein to the plasma membrane instead of to the ER. It also became clear that misfolded protein was forming oligomers with wild-type GnRHR protein, effectively rendering the latter useless and a target for the quality control machinery of the cell. It is concluded that small molecules (e.g., 1N3) can be tried for the treatment of genetic diseases associated with misfolded proteins. A different type of autophagy protein, intrinsically disordered or unstructured protein, is discussed below. Some autophagy proteins (Atgs) have intrinsically disordered regions (IDRs). The latter are called IDRPs, which are predicted in ~30% of the prokaryotic proteins and ~47% of eukaryotic proteins (Dunker et al., 2008). IDRPs have negligible folded tertiary structure or stable secondary structure elements such as α-helix and β-sheets. The importance of the IDRs in cellular processes has been overlooked, as biological roles and mechanisms of most of these regions are poorly understood. These regions play an important role in autophagy, and this role has not been adequately investigated.


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IDRPs in contrast to Atgs are poorly conserved. IDRs seem to have diverse functions in different homologs. Recent studies indicate that IDRs facilitate protein–protein interactions (Mei et al., 2014). The importance of this role becomes apparent considering that many or even most Atgs function via formation of multiprotein complexes. These complexes initiate autophagy, autophagosome nucleation, and autophagosome expansion, maturation, and fusion with lysosomes. Potential protein partners that might interact with the disordered regions have been identified (Mei et al., 2014). For example, a Bcl2 homology 3 domain (BH3D) (within the key autophagy Beclin 1 protein) is an IDR. BH3D undergoes a conformational change from coil to α-helix upon binding to Bcl2. The C-terminal half of this BH3D constitutes the binding motif, which serves to anchor the interaction of the BH3D to Bcl2. Finally the high preponderance of IDRs in autophagy proteins implies that these regions play a significant role in the autophagic functions. It needs to be noted that mutations implicated in major diseases, including cancer and neurodegenerative and cardiovascular disorders, map to IDRs (Uversky et al., 2008).

Molecular Chaperones Molecular chaperones (heat shock proteins, Hsps) help misfolded proteins to correctly fold by binding to their hydrophobic surfaces. The chaperones are called Hsps because they are synthesized in increased amounts after cells are briefly exposed to high temperatures or any other types of stress, for example, ER stress. Elevated temperatures cause an increase in misfolded proteins, which, in turn, results in a feedback system that boosts the synthesis of chaperones, helping the misfolded proteins to refold. The best relevant eukaryotic chaperones are Hsp60 and Hsp70. Different members of the chaperone family function in different organelles and locations; for example, mitochondria contain their own Hsp60 and Hsp70 molecules, which differ from those that function in the cytosol. A large number of chaperone proteins, foldases, and cofactors are expressed at the ER to promote correct folding and prevent abnormal aggregation of misfolded proteins. The existence of chaperones implies that some proteins have inherently unstable conformation that can change from a functional minimal energy state to a state that is nonfunctional or even toxic. One of the most abundant chaperones in the ER lumen is a protein called Bip (binding protein), which is a member of the Hsp70 family of proteins. Bip binds to hydrophobic regions of the polypeptide chain, especially those enriched in the amino acids tryptophan, phenylalanine, and leucine. In contrast, in a correctly folded protein, such hydrophobic regions are aggregated and buried in the interior of the protein molecule and inaccessible to Bip. Bip recognizes newly synthesized proteins as they are translocated in the ER and maintains them in a state of competent for subsequent folding and oligomerization. Although chaperones help unstable proteins to fold correctly, some proteins remain misfolded and may form long linear or fibrillary aggregates known as amyloid deposits, including those in AD.

The ER The ER is the main compartment where most of the proteins are synthesized and folded. Free ribosomes (not attached to the ER) are also involved in the synthesis of some proteins.


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Free ribosomes are especially active in synthesizing proteins that are retained within the cell, while ribosomes of the ER synthesize mainly proteins that are exported from the cell. Most of the proteins synthesized on ER ribosomes are glycoproteins. The glycosylation takes place in the ER while the growing polypeptide chain is still being synthesized. A typical eukaryotic cell has its own unique set of proteins in billions, representing at least 10,000 different kinds of polypeptides, each of these proteins finds its way either to the appropriate location within the cell or out of the cell. The cell has quality control mechanisms that ensure that proteins are folded into their correct three-dimensional conformation before they can move from the ER to the appropriate destination in the cell (protein trafficking). Misfolded proteins are often eliminated by the quality control mechanisms after initially being retained in the ER instead of being immediately eliminated. The retention of misfolded proteins in the ER interrupts their proper trafficking, and the resulting reduced biological activity can lead to impaired cellular function, and ultimately to disease. An interesting recent study by Cortes et al. (2013) demonstrated the intracellular trafficking and the degradation of newly synthesized misfolded/aggregated mutant PrP. They found that autophagy plays a key role in delivering such proteins from the ER to lysosomes. In the absence of such quality control mechanism to limit the accumulation of misfolded PrP, it may lead to the generation of a pathologic misfolded isoform (PrPsc) causing genetic prion disease. This concept is strengthened by the finding that in normal cells treated with the autophagy inhibitor 3-MA, mutant-PrP colocalization with lysosomes is reduced. Additionally, mut-PrP expression is associated with an elevation of several markers of the autophagy-lysosome pathway, and is extensively localized with the autophagic-specific marker, LC3B. The accumulation of misfolded proteins in the ER may lead to various types of stress on cells, which may contribute to cellular dysfunction and disease such as neurodegenerative conditions. As stated earlier in this chapter, a number of stress conditions can interfere with the function of this organelle, and cause abnormal oxidative folding in the ER lumen, resulting in a cellular condition called ER stress. ER stress engages the UPR, an integrated signal transduction pathway that reestablishes homeostasis by increasing the protein folding capacity and quality control mechanisms of the ER. The UPR is activated by three main stresses such as PERK, inositol-requiring transmembrane kinase/endonuclease (ITRE1), and ATF6.

ER and Apoptosis ER stress activates the UPR, which alleviates this stress by promoting protein folding and clearance to reduce the amount of misfolded proteins at the ER. However, chronic ER stress may result in apoptosis of irreversibly damaged cells through diverse complimentary mechanisms. One such mechanism involves the canonical mitochondrial apoptosis pathway, where the Bcl-2 family plays an important role (Shore et al., 2011). Under irreversible ER stress a switch from the adaptive UPR to proapoptotic signaling seems to occur. Although the exact underlying molecular mechanism of this switch is not clear, ER calcium release, Bcl-2 family of proteins, microRNA, and oxidation stress are involved (Urra et al., 2013).


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AUTOPHAGIC PROTEINS Cells assure the renewal of their constituent proteins through a continuous process of synthesis and degradation that also allows for rapid modulation of the levels of specific proteins to accommodate to the changing extracellular environment. Intracellular protein degradation is also essential for cellular quality control to eliminate damaged or altered proteins, preventing the toxicity associated with their accumulation inside cells. Autophagy essential proteins are the molecular basis of protective or destructive autophagy machinery. Some information is available regarding the signaling mechanisms governing these proteins and the opposing consequences of autophagy in mammals. Genes responsible for the synthesis of these proteins are summarized here. Autophagy was first genetically defined in yeast, where 31 genes, referred to as autophagy-related genes (Atg), were identified as being directly involved in the execution of autophagy (Mizushima, 2007; Xie and Klionsky, 2007). At least 16 members of this gene family have been identified in humans. The role of a large number of these genes has been deciphered. Our understanding of the molecular regulation of autophagy process originates from the characterization of these genes and proteins in yeast, many of which have counterparts in mammals. The core autophagic machinery comprises 18 Atg proteins, which represent three functional and structural units: (1) the Atg9 cycling system (Atg9, Atg1 kinase complex (Atg1 and Atg13), Atg2, Atg18, and Atg27); (2) PI3K complex (Atg6/Vps30), Atg14, Vps15, and Vps34; and (3) ubiquitin-like protein system (Atg3-5, Atg7-8, Atg10, Atg12, and Atg 16) (Minibayeva et al., 2012). In addition to these core Atg proteins, 16 other proteins are essential for certain pathways or in different species. An alternate abbreviated system of Atg proteins follows. Autophagic proteins generally function in four major groups: the Atg1 kinase complex, the Vps34 class III phosphatidylinositol 3-kinase complex, two ubiquitin-like conjugation systems involving Atg8 and Atg12, and a membrane-trafficking complex involving Atg9 (Florey and Overholtzer, 2012). In mammalian cells the key upstream kinase that regulates the induction of most forms of autophagy is the Atg1 homology Ulk1, which forms a complex with Atg13, Fip200, and Atg101. Among the Atg proteins, Atg9 is the only multispanning membrane protein essential for autophagosome formation. It needs to be noted that autophagy proteins are also involved in nonautophagic functions such as cell survival, apoptosis, modulation of cellular traffic, protein secretion, cell signaling, transcription, translation, and membrane reorganization (Subramani and Malhotra, 2013).

Protein Degradation Systems There are two major protein degradation pathways in eukaryotic cells, i.e., ubiquitin proteasome and autophagy-lysosome systems. Both of these systems are characterized by selective degradation. UPS is responsible for degradation of short-lived proteins and is involved in the regulation of various cellular signaling pathways. Autophagy is a regulatory mechanism for degrading large proteins having longer half-life, aggregates, and defective cellular organelles. Ubiquitin-binding proteins, such as p62 and NBR1, regulate autophagy dynamics.


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These adaptor proteins decide the fate of protein degradation either through UPS or through autophagy-lysosome pathway. Many degenerative conditions such as Huntington’s, Parkinson’s, Alzheimer’s, amyotrophic lateral sclerosis, and diabetes are due to defective clearance of mutated protein aggregates or defective organelles through autophagy.

Beclin 1 Beclin 1 (from Bcl-2 interacting protein) is a 60-kDa coiled-coil protein that contains a Bcl-2 homology-3 domain, a central coiled-coil domain, and an evolutionary conserved domain. Beclin 1 was originally discovered not as an autophagy protein but as an interaction partner for the antiapoptotic protein Bcl-2. The function of Beclin 1 in autophagy was first suspected due to its 24.4% amino acid sequence identity with the yeast autophagy protein Atg6. Beclin 1 was found to restore autophagic activity in Atg6-disrupted yeast, becoming one of the first identified mammalian genes to positively regulate autophagy. Subsequent studies demonstrated that Beclin 1 is a haploinsufficient tumor-suppressor gene that is either monoallelically deleted or shows reduced expression in several different cancers (Yue et al., 2003). Beclin 1 is also involved in several other biological functions and in human conditions including heart disease, pathogen infections, development, and neurodegeneration. These functions will not be discussed here because only the role of this gene (protein) in autophagy is relevant here. The central role of Beclin 1 complexes is in controlling human Vps34-mediated vesicle trafficking pathways including autophagy. Beclin 1 and its binding partners control cellular Vps34 lipid kinase activity that is essential for autophagy and other membrane trafficking processes, targeting different steps of the autophagic process such as autophagosome biogenesis and maturation (Funderburk et al., 2010). Beclin 1-depleted cells cannot induce autophagosome formation. In conclusion the crucial regulator of autophagy is Beclin 1 (the mammalian homolog of yeast Atg6), which forms a multiprotein complex with other molecules such as UVRAG, AMBRA-1, Atg14L, Bif-1, Rubicon, SLAM, IP3, PINK, and survivin; this complex activates the class III phosphatidylinositol-3-kinase (Petiot et al., 2000).

Nonautophagic Functions of Autophagy-Related Proteins The importance of nonautophagic biological functions of autophagy-related proteins is beginning to be realized. These proteins (e.g., ubiquitin-like proteins Atg8 and Atg12) play an important role in various aspects of cellular physiology, including protein sorting, DNA repair, gene regulation, protein retrotranslation, apoptosis, and immune response (Ding et al., 2011a). These proteins also play a role in cell survival, modulation of cellular traffic, protein secretion, cell signaling, transcription, translation, and membrane reorganization (Subramani and Malhotra, 2013). Apparently, these proteins and their conjugates possess a different, broader role that exceeds autophagy. The interactions of ubiquitin-like proteins with other autophagy-related proteins and other proteins are summarized below. For example, six Atg8 orthologues in humans interact with at least 67 other proteins. Nonautophagy-related proteins, which interact with Atg8


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and LC3 include GTPases, affect cytoskeletal dynamics, cell cycle progression, cell polarity, gene expression, cell migration, and cell transformation (Ding et al., 2011a). Nonlipidated LC3 and nonlipidated Atg8 regulate viral replication and yeast vacuole fusion, respectively (Tamura et al., 2010). Atg5 and Atg12-Atg5 conjugates suppress innate antiviral immune signaling. Based on these and other functions, ubiquitin-like proteins in their conjugated and unconjugated forms modulate many cellular pathways in addition to their traditional role in autophagy (Subramani and Malhotra, 2013). In addition to ubiquitin-like Atg proteins, other Atg-related proteins are also involved in nonautophagic functions that are summarized below. UNC-51, the homologue of human ULK1, regulates axon guidance in many neurons. Atg16L1 positively modulates hormone secretion in PC12 cells, independently of autophagic activity (Ishibashi et al., 2012). Atg16L1, Atg5, Atg7, and LC3 are genetically linked to susceptibility to Crohn’s disease, a chronic inflammation condition of the intestinal tract (Cadwell et al., 2009). Atg5, Atg7, Atg4B, and LC3 are involved in the polarized secretion of lysosomal enzymes into an extracellular resorptive space, resulting in the normal formation of bone pits or cavities (bone resorption) (DeSelm et al., 2011). Considering a wide variety of functions of Atg-related proteins in typical nonautophagic cellular activities (some of which are enumerated here) indicate that the autophagic machinery is enormously complex and more versatile than presently acknowledged. Indeed much more effort is needed to better understand the role of this machinery in health and disease, which eventually may allow us to delay the aging process and provide us with effective therapeutics.

Microtubule-Associated Protein Light Chain 3 Microtubule-associated light chain 3 (LC3) is a mammalian homologue of yeast Atg8. It was the first mammalian protein discovered to be specifically associated with autophagosomal membranes. Although LC3 has a number of homologues in mammals, LC3B is most commonly used for autophagy (macroautophagy) assays because it plays an indispensable role in autophagosome formation, making it a suitable marker for this process. The cytoplasm contains not only LC3I but also an active form (LC3-II). Immediately after synthesis of the precursor protein (pro-LC3), hAtg4B cleaves a C-terminal 22-amino acid fragment from this precursor form to the cytosolic form LC3-I. After, LC3-I is transiently conjugated to membrane bound PE to generate LC3-II, which localizes in both the cytosolic and intralumenal faces of autophagosomes. Because of its essential role in the expansion step of autophagosome formation, LC3-II is regarded as the most reliable marker protein for autophagy. Following fusion with lysosomes, intralumenally located LC3-II is degraded by lysosomal hydrolases, and cytosolically oriented LC3-II is delipidated by hAtg4B, released from the membrane, and finally recycled back to LC3-I (Karim et al., 2007). Divergent roles of LC3 (or Beclin1) in tumorigenesis have been reported. For example, LC3 expression is either decreased in brain cancer (Aoki et al., 2008) and ovary cancer (Shen et al., 2008) or increased in esophageal and gastrointestinal neoplasms (Yoshioka et al., 2008). LC3 is also associated with poor outcome in pancreatic cancer, whereas its expression is associated with a better survival in glioblastoma patients with poor performance score (Aoki et al., 2008). It has also been reported that LC3-11 protein expression is inversely correlated with


Aggrephagy

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melanoma thickness, ulceration, and mitotic rate (Miracco et al., 2010). These and other studies imply that clinical impact of LC3 is associated with the tumor type, tissue context, and other factors.

AGGREPHAGY The term aggrephagy was introduced by Øverbye et al. (2007). Protein aggregation begins with misfolded proteins forming oligomeric intermediates, which can mature initially into small protein aggregates, some of which continue to multimerize into aggregates (clumps) of a large size. Both newly formed and preexisting polypeptide chains resulting from genetic mutations, inappropriate protein assembly, aberrant modifications, and environmental stresses are inevitable byproducts of biogenesis (Kazami et al., 2011). An aggresome, essentially, is a protein complex containing abnormal proteins, chaperone proteins, proteasome components, mitochondrial components, and ubiquitinated proteins. Proteins of aggresomes are usually ubiquitinated, insoluble, and metabolically stable. Certain other types of aggresome proteins are located at the cell periphery and do not contain ubiquitin (Kaganovich et al., 2008). Protein aggregation in cells is not a simple, random process resulting from uncontrolled interaction among inappropriately exposed hydrophobic surfaces. Some information explaining the formation of protein aggregates is presented below; additional information regarding protein aggregation is found under “Protein Synthesis” section in this chapter. Aggresomes are formed in response to proteasomal inhibition or overexpression of aggregation-prone proteins and are located near the nuclear envelope at the microtubule organizing center. The formation of aggresomes depends on the microtubule-depended transport of protein aggregates (Kopito, 2000). Microtubules-associated histone deacetylase 6 (HDAC6) mediates this process. Through its ubiquitin-binding BUZ finger domain, HDAC6 binds to and facilitates the transport of polyubiquitinated misfolded proteins along microtubules to aggresome (Kawaguchi et al., 2003). Aggregated proteins are toxic, and so their efficient disposal is essential for cell survival. To protect cells from potentially deleterious effects of aggregated proteins, aggresomes are formed to sequester such proteins. Aggresome formation is an active response to cope with excessive levels of misfolded and aggregated proteins. The formation of aggresomes is a second line of active cellular defense. Aggresome formation, in addition, allows the clearance of misfolded proteins by alternative protein quality control systems such as the autophagy-lysosome pathway. An interesting scheme explaining the formation of protein aggregates in HeLa cells and nonsmall lung cancer cells was proposed by Mi et al. (2009). They indicate that cancer chemopreventive ITCs binding to tublin triggers the formation of protein aggregates. This small molecule covalently modifies specific cysteine residues in tubulins, causing transformational changes and misfolding of proteins. Cells carry out their various functions by synthesizing and degrading proteins on a regular basis. The routine degradation of abnormal (misfolded) and unwanted (excessive) proteins are accomplished primarily by the UPS. The aggregation of misfolded proteins tends to cause problems in the cell. They can damage cells and tissues, and may also cause disorders, including neurodegenerative diseases and type II diabetes. To circumvent such


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problems and maintain quality control, cells have developed efficient mechanisms to target and eliminate such proteins, which are discussed elsewhere in this chapter. It is difficult to distinguish correctly folded proteins from misfolded proteins of any particular type because both are composed of the same basic amino acid sequence. These two types of proteins differ from each other only in the final three-dimensional folded structures. Some fundamental questions that still remain to be answered are (Lamark and Johansen, 2012): Which size of protein aggregates are degraded by selective autophagy? Is there a maximum size of the aggregates that can be degraded? Are the large aggregates degraded whole-sale or dismantled into small aggregates prior to their engulfment by autophagosomes? What are the differences and similarities between different types of protein aggregates? How should different types of protein aggregates be classified? Is the degradation of large size protein aggregates most efficiently carried out by a combination of UPS, CMA, and autophagy? Can aggrephagy be modulated as a therapeutic strategy for neurodegenerative diseases and other proteinopathies?

Aggresome, Ubiquitin Proteasome, and Autophagic Systems The UPS removes nonfunctional damaged, and misfolded, proteins from the cell. When the capacity of the proteasome is impaired and/or when the amounts of such proteins exceed the capacity of proteasome, they accumulate into the aggresome. Aggresome formation is a cytoprotective response to sequester potentially toxic misfolded proteins and facilitate their clearance by autophagy, which is related to the UPS and autophagic protein degradation mechanism. Both Parkin and Parkin-coregulated gene (PACRG) function in aggresome formation and turnover. It has been suggested that this gene functions as a sensor mechanism for the UPS (Taylor et al., 2012). The UPS removes nonfunctional, damaged, and/or misfolded proteins from the cell. When the capacity of the proteasome is impaired and/or when the amount of misfolded proteins exceeds the capacity of proteasome, they accumulate in the form of aggresomes. Aggresome removal is mediated by ubiquitin-binding proteins such as p62/SQSTM1 and NBR1. These adaptor proteins through their ubiquitin-binding protein (UBA) are responsible for the fate of protein degradation either through UPS or through autophagy (Komatsu and Ichimura, 2010a,b). E3-ubiquitin ligases play a key role in the execution of autophagy (Chin et al., 2010). Recently, it was reported that in response to proteasome inhibition, the E3-ubiquitin ligase TRIM50 localizes and promotes the recruitment and aggregation of polyubiquitinated proteins to the aggresome (Fusco et al., 2012). They showed that TRIM50 colocalizes, interacts with, and increases the level of p62 that is a multifunctional adaptor protein involved in various cellular processes, including the autophagic clearance of polyubiquitinated protein aggregates. The implication of this information is that in the absence of proteasome activity, TRIM50 fails to drive its substrates to the proteasome-mediated degradation and promotes their storage in the aggresome for subsequent removal by p62-mediated autophagy. It is known that the accumulation of polyubiquitinated protein aggregates is associated with neurodegenerative disorders and other protein aggregation diseases. It is also known that p62 is a component of inclusion bodies in neurodegenerative diseases and liver diseases.


Reactive Oxygen Species

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MONITORING AUTOPHAGY A number of methods are available to monitor autophagy, which can be accomplished by using electron microscopy, fluorescent microscopy, biochemical protocols, and detection of relevant protein modifications through SDS-PAGE and Western blotting. Autophagy can be monitored by detecting autophagosomal proteins such as LC3. LC3 is a specific marker protein of autophagic structure in mammalian cultured cells. The appearance of this proteinpositive puncta is indicative of the induction of autophagy. One of such methods consists of monitoring autophagy by detecting LC3 conversion from LC3-I to LC3-II by immunoblot analysis because the amount of LC3-II is clearly correlated with the number of autophagosomes. Endogenous LC3 is detected as two bands following SDS-PAGE and immunoblotting: one represents cytosolic LC3-I and the other LC3-II that is conjugated with PE, which is present on isolation membranes and autophagosomes, but much less on autolysosomes (Mizushima and Yoshimori, 2007). According to Kadowaki and Karim (2009), LC3-1 to LC3-11 ratio in the cytosol (cytosolic LC3 ratio), but not in the homogenate, is an easy quantitative method for monitoring the regulation of autophagy. Alternatively, comparison of LC3-II levels between different conditions is a useful method for monitoring autophagy. Another approach is the fluorescent protein, GFP-LC3, which is a simple and specific marker. To analyze autophagy in whole animals, GFP-LC3 transgenic mice have been generated (Mizushima and Kuma, 2008). However, the GFP-LC3 method does not provide a convenient measure for assessing autophagic flux. Therefore, another alternative method, tandem fluorescent-tagged LC# (tfLC#) can be used to monitor autophagic flux (Kimura et al., 2009). In spite of the advantages of the LC3 method, it has some limitations. LC3 protein, for example, tends to aggregate in an autophagy-independent manner. LC3-positive dots seen in the light microscope after using the transfected GFP-LC3 method may represent protein aggregates, especially when GFP-LC3 is overexpressed or when aggregates are found within cells (Kuma et al., 2007). LC3, in addition, is easily incorporated into intracellular protein aggregates, e.g., in autophagy-deficient hepatocytes, neurons, or senescent fibroblasts. Also, LC3 is degraded by autophagy. In the light of above limitations, it is important to measure the amount of LC3-II delivered to lysosomes by comparing its levels in the presence or absence of lysosomal protease inhibitors such as E64d and pepstatin A (Mizushima and Yoshimori, 2007). These authors have pointed out pitfalls and necessary precautions regarding LC3 immunoblot analysis. A very extensive update of the assays for monitoring autophagy has been presented by Klionsky et al. (2012); they strongly recommend the use of multiple assays to monitor autophagy and presents 17 methods for monitoring autophagy.

REACTIVE OXYGEN SPECIES ROS are highly reactive forms of molecular oxygen, which include superoxide anion radical, hydrogen peroxide, singlet oxygen, and hydroxyl radical (Park et al., 2012). ROS are generally produced during normal metabolism of oxygen inside the mitochondrial matrix that acts as the primary source of them. Basal levels of ROS serve as physiological regulators


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of normal cell multiplication and differentiation. If the balance of ROS increases more than the scavenging capacity of the intracellular antioxidant system, the cell undergoes a state of oxidative stress with significant impairment of cellular structures. Excessive levels of ROS, for example, can cause severe damage to DNA and proteins. The oxidative stress specially targets mitochondria, resulting in the loss of mitochondrial membrane potential and initiating mitochondria-mediated apoptosis. Oxidative stress can also lead to the autooxidation of sterols, thereby affecting the cholesterol biosynthetic pathway, mainly the postlanosterol derivatives. The intracellular accumulation of oxysterols directs the cell to its autophagic fate and may also induce it to differentiate. ROS, in fact, can play contrasting roles: they can initiate autophagic cell death and also function as a survival mechanism through induction of cytoprotective autophagy in several types of cancer cells.

MAMMALIAN TARGET OF RAPAMYCIN The mammalian target of rapamycin (mTOR), also known as mechanistic target of rapamycin or FK506-binding protein 12-rapamysin-associated protein 1 (FRAP1), is ~a 289-kDa protein originally discovered and cloned from Saccharomyces cerevisiae that shares sequence homologies with the PI3-kinase family, which is the key element in response to growth factors. mTOR represents a serine threonine protein kinase that is present in all eukaryotic organisms (Wullschleger et al., 2006). mTOR represents the catalytic subunit of two distinct complexes; mTORC1 and mTORC2 (Zoncu et al., 2011). mTORC1 controls cell growth by maintaining a balance between anabolic processes (e.g., macromolecular synthesis and nutrient storage) and catabolic processes (e.g., autophagy and the utilization of energy stores) (Nicoletti et al., 2011). The receptor-mTOR complex positively regulates cell growth, and its inhibition causes a significant decrease in cell size. The raptor part of the mTOR pathway modulates a large number of major processes that are listed here. Rapamycin binds to the FKBP12 protein, forming a drug-receptor complex, which then interacts with and perturbs TOR. TOR is the central component of a complex signaling network that regulates cell growth and proliferation. The components of these complexes exist in all eukaryotes. As indicated earlier, mTOR is a major cellular signaling hub that integrates inputs from upstream signaling pathways, including tyrosine kinase receptors that play a key role in intracellular nutrient sensoring. It serves as the convergent point for many of the upstream stimuli to regulate cell growth and nutrient metabolism, cell proliferation, cell motility, cell survival, ribosome biosynthesis, protein synthesis, mRNA translation, and autophagy (Meijer and Codogno, 2004). Two mammalian proteins, S6 kinase and 4E-BP1, link raptormTOR to the control of mRNA translation (Sarbassov et al., 2005). mTOR also governs energy homeostasis and cellular responses to stress such as nutrient deprivation and hypoxia. Many studies have demonstrated that Akt/mTOR-dependent pathway is involved in the process of chemical (platinum)-induced autophagy, in which mTOR is a pivotal molecule in controlling autophagy by activating mTOR (Hu et al., 2012). Another recent investigation also shows that methamphetamine (METH) causes damage to PC12 cells, but this damage can be decreased by using a supplement of taurine via inhibition of autophagy, oxidative stress, and apoptosis (Li et al., 2012).


Role of Autophagy in Tumorigenesis and Cancer

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Abundance of nutrients, including growth factors, glucose, and amino acids activate mTOR and suppress autophagy, while nutrients deprivation suppresses mTOR, resulting in autophagy activation. In other words, triggering of autophagy relies on the inhibition of mammalian mTOR, an event that promotes the activation of several autophagy proteins (Atgs) involved in the initial phase of membrane isolation. Among many signaling pathways controlling mTOR activation, PI3K is the key element in response to growth factors. mTORC1 and Atg1/ULK complexes constitute the central axis of the pathways that coordinately regulates growth and autophagy in response to cellular, physiological and nutritional conditions. The negative regulation of mTORC1 by Atg1/ULK stresses further the intimate cross talk between autophagy and cell growth pathways (Jung et al., 2010). The role of mTOR in aging is discussed separately in this chapter.

ROLE OF AUTOPHAGY IN TUMORIGENESIS AND CANCER Malignant neoplasms constitute the second most common cause of death in the United States, and malignant brain tumors contribute 2.4% of cancer related deaths. An estimated 20,340 new cases of primary central nervous system tumors were diagnosed (2012) in the United States alone and resulted in approximately 13,110 deaths. Despite considerable advances in multimodel treatment of tumors in the last five decades, there has been only a minimal improvement in the median survival time of brain malignant patients. Causative factors for the poor survival rate include the highly invasive nature of brain malignant tumors making them intractable to complete surgical resection, and resistance to standard chemotherapy and radiotherapy. This difficulty to remedy cancer underscores the need to pursue prosurvival signaling mechanisms that contribute to the resistance of cancer development; such alternative therapies include the use of autophagy. Cancer is associated with aging, for more than 80% of human cancers are diagnosed in people aged 55 years or older. Humans and other mammals with long life spans unfortunately have to face the problem of the accumulation of somatic mutations over time. Some of these mutations cause diseases that eventually lead to the demise of the individual. Cancer is one of these major diseases, which is caused by a combination of somatic, genetic alterations in a single cell, followed by uncontrolled cell growth and proliferation. Even a single germline deletion or mutation of a tumor suppressor gene predisposes an individual to cancer. It is apparent that nature tried to ensure the longevity of the individual by providing tumor suppressor genes and other protective machineries. Autophagy (e.g., Beclin 1 gene) is one of these machineries, which plays an important role in influencing the aging process. Autophagy defects are linked to many diseases including cancer, and its role in tumorigenesis is exceedingly complex, and is tissue-and genetic context-dependent. Metabolically stressed tumor cells rely on autophagy for survival and reprogramming of their metabolism to accommodate rapid cell growth and proliferation (Lozy and Karantza, 2012). To accomplish this goal, specific catabolic reactions (e.g., aerobic glycolysis and glutaminolysis) are upregulated for providing needed energy and rebuilding new complex macromolecules such as proteins, nucleic acids, and lipids.


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Autophagy has complex and paradoxical roles in antitumorigenesis, tumor progression, and cancer therapeutics. Initially, two principal lines of evidence connected autophagy and cancer. (1) It was found that BECN1 gene is monoallelically deleted in several types of cancers. (2) Autophagy not only can function to promote tumor cell survival but can also contribute to cell death. In other words, autophagy can be both tumorigenic and tumor suppressor. Exact role in each case is dependent on the context and stimuli. Autophagy can be upregulated or suppressed by cancer therapeutics, and upregulation of autophagy in cancer therapies can be either prosurvival or prodeath for tumor cells. It is known that autophagy maintains cellular integrity and genome stability. Loss of autophagy genes perturbs this homeostasis, thereby potentially priming the cell for tumor development. The following autophagy genes are mutated in some cancers (Liu and Ryan, 2012): BECN1, UVRAG, SH3GLB1 (Bif-1), ATG2B, ATG5, ATG9B, ATG12, and RAB7A. Mutations in ATG2B, ATG5, ATG9B, and ATG12 have been reported in gastric and colorectal cancers (Kang et al., 2009). The expression of Bif-1 is downregulated in gastric and prostate cancers (Takahashi et al., 2010). Mutations of UVRAG have been found in colon cancer (Knaevelsrud et al., 2010). Autophagy is associated with both cancer progression and tumor suppression. Some of the molecular mechanisms underlying these two phenomena have been elucidated. It is known that cancer cells generally tend to have reduced autophagy compared with their normal counterparts and premalignant lesions. Therefore, for autophagy to induce cancer progression, it will have to be activated. This is accomplished, for example, by the KRAS oncogene that is known to induce autophagy. It has been shown that autophagy is activated constitutively in oncogenic KRAS-driven tumors and that this cellular event is required for the development of pancreatic tumors (Yang et al., 2011). The discovery that autophagic-related gene BECN1 suppresses tumor growth stimulated significant interest from cancer biologists in this previously unexplored therapeutic process. This interest has resulted in both intensive and extensive research efforts to understand the role of autophagy in cancer initiation, progression, and suppression. Pharmacological or genetic inactivation of autophagy impairs KRAS-mediated tumorigenesis. It has been shown that transmembrane protein VMP1 (vacuole membrane protein 1) (a key mediator of autophagy) is a transcriptional target of KRAS signaling in cancer cells (Lo Ré et al., 2012). It regulates early steps of the autophagic pathway. In fact, KRAS requires VMP1 not only to induce but also to maintain autophagy levels in cancer. PI3K-AKT1 is the signaling pathway mediating the expression and promoter activity of VMP1 upstream of the GLI3-p300 complex. The BECN-1 gene is deleted in ~ 40% of prostate cancer, 50% in breast cancer, and ~75% in ovarian cancer (Liang et al., 1999). In addition, reduced expression of Beclin-1 has been found in other types of cancers including human colon cancer, brain tumors, hepatocellular carcinoma, and cervical cancer. It can be concluded that a defective autophagic process is clearly linked to cancer development. Autophagy is associated with resistance to chemotherapeutics such as 5-flurouracil and cisplatin. It is recognized that tumors and the immune systems are intertwined in a competition where tilting the critical balance between tumor-specific immunity and tolerance can finally determine the fate of the host (Townsend et al., 2012). It is also recognized that defensive and suppressive immunological responses to cancer are delicately sensitive to metabolic features of rapidly growing tumors.


Autophagy and Immune System

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On the other hand, autophagy may increase the effectiveness of anticancer radiotherapy. It is known that some malignancies become relatively resistant to repeated radiotherapy and may eventually recover self-proliferative capacity. This problem can be diminished by inducting autophagy through Beclin 1 overexpression in conjunction with radiotherapy. It is known that autophagy enhances the radiosensitization of cancer cells rather than protecting them from radiation injury and cell death. It is also known that autophagy inhibits the growth of angiogenesis in cancer cells. It should also be noted that autophagic cell death may occur in some cancer types in response to various anticancer drugs. In other words, autophagy may serve as a pathway for cellular death. Based on the two opposite roles of autophagy, it is poised at the intersection of life and death. However, an agreement on the cellular death is lacking because of the absence of functional evidence. It is apparent that we need to understand and modulate the autophagy pathway to maximize the full potential of cancer therapies. As mentioned earlier, autophagy is frequently upregulated in cancer cells following standard treatments (chemotherapy, radiotherapy), showing prosurvival or prodeath for cancer cells (reviewed by Liu and Ryan, 2012). Treatment with rapamycin, rapamycin analogues, and imatinib shows prodeath effect, while treatment with radiation, tamoxifen, camptothecan, and proteasome inhibitors results in the survival of cancer cells. Effect of autophagy seems to be different in distinct tumor types, at various stages of tumor development, and even within different regions of the same tumor. It is concluded that generally either overactivation or underactivation of autophagy contributes to tumorigenesis, and that autophagy limits tumor initiation, but promotes establishment and progression.

AUTOPHAGY AND IMMUNE SYSTEM Autophagy, immunity, and aging are mutually interconnected. The linkage of autophagy with immunity most probably began early in the evolutionary process. In fact, autophagy probably formed the most ancient of immune defenses. It is likely that in the early evolution of eukaryotic cells, “autophagy” played a key role in the cytosolic protection from invading foreign organisms. The remnant of such a primitive immune system may be equated with the removal of dysfunctional mitochondria by autophagy (mitophagy). It has been suggested that mitochondria have evolved from a Rickettsia-like alpha-protobacterium that was foreign to the eukaryotic cells a long time ago (Deretic, 2010). The survival of such “bacteria” and the need of energy made it necessary to develop a symbiotic relationship between such pathogens and eukaryotic organisms. Both autophagy and immunology are involved in the defense of the organism, including against pathogens; xenophagy is discussed separately in this chapter. The interplay between autophagy and innate and adaptive immunity is well-established, and the role of autophagy in infection, inflammation, and immunity has been detailed (Deretic et al., 2013). The role of autophagy in a variety of diseases has been known for a long time; e.g., the role of autophagy gene Atg16l1 mutation in Crohn’s disease was reported in 2008 by Cadwell et al. (2008). Another example is the link between autophagy-independent functions of autophagy related proteins (Atgs) and phagocytosis (Sanjuan et al., 2007). The role of autophagy in neurodegenerative diseases connected with aging is well-known and is discussed elsewhere in this chapter.


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The eradication of invading pathogens is essential to multicellular organisms including humans. During the past two decades, there has been a rapid progress in the understanding of innate immune recognition of microbial components and its critical role in host defense against infection. The innate immune system is responsible for the initial task of recognizing and destroying potentially dangerous pathogens. Innate immune cells display broad antimicrobial functions that are activated rapidly upon encountering microorganisms (Franchi et al., 2009). Autophagy can also function as a defense by the cell against intracellular pathogens. Autophagy is involved in almost every key step from the recognition of a pathogen to its destruction and the development of a specific adaptive immune response to it. Autophagy, in addition, controls cell homeostasis and modulates the activation of many immune cells, including macrophages, dendritic cells, and lymphocytes, where it performs specific functions such as pathogen killing or antigen processing and presentation (Valdor and Macian, 2012). The autophagy pathway is linked to one or more aspects of immunity. Studies have shown that autophagy is regulated by these pathways that are critical for the function and differentiation of cells of the immune system, including Toll-like receptors (TLRs). TLRs were the first class of immune receptors identified as regulators in cells of the innate immune system. They play a crucial role in many aspects of the immune response. They are broadly expressed in immune cells, particularly in antigen-presenting cells, and recognize pathogen-associated molecular patterns such as lipopolysaccharides, viral double-stranded RNA, and unmethylated CpPG islands (Harashima et al., 2012). Initiation of TLR signaling induces release of inflammatory cytokines, maturation of dendritic cells, and activation of adaptive immunity. Cancer cells also express functional TLRs. TLR4 signaling, for example, promotes escape of human lung cancer cells from the immune system by inducing immune suppressive cytokines and promoting resistance to apoptosis (He et al., 2007). In contrast, TRL3 signaling induces antitumor effects. Akt activation can render cancer cells resistance to antitumor cellular immunity (Hähnel et al., 2008). The implication is that Akt inactivation increases the susceptibility of cancer cells to immune surveillance. TLRs also have been shown to induce autophagy in several cell types, including neutrophils (Xu et al., 2007). The activation of the TLR-downstream signaling proteins MyD88 and Trif appears to be involved in the induction of autophagy. These proteins are recruited together with Beclin 1 to TLR4, which promotes the dissociation of Beclin 1/Bcl2 complex and induces autophagosome formation (Shi and Kehri, 2008). MyD88 and Trif target Beclin 1 to trigger autophagy in macrophages. TLRs have also been shown to promote a process involving the autophagy machinery termed LC3-associated phagocytosis (Valdor and Macian, 2012). The uptake of cargo containing TLR ligands by macrophages leads to the recruitment of LC3 on the phagosome surface, promoting the degradation of the pathogens by enhancing phagosome–lysosome fusion in the absence of autophagosome formation (Sanjuan et al., 2009). In fact, the study of TLRs showed that pathogen recognition by the innate immune system is specific, relying on germline-encoded pattern-recognition receptors that have evolved to detect components of foreign pathogens (Akira et al., 2006). TLRs recognize conserved structures in pathogens, which leads to the understanding of how the body senses pathogen invasion, triggers innate immune responses, and primes antigen-specific adaptive immunity


Role of Autophagy and Cellular Senescence in Aging

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(Kawai and Akira, 2010). The adaptive immune system relies on a diverse and specific repertoire of clonally selected lymphocytes. Additional studies are needed to better understand the mechanisms that regulate autophagy in immune cells and the role this process plays in the establishment of immune responses against foreign pathogens.

AUTOPHAGY AND SENESCENCE Cellular senescence is a biological state in which cells have lost the ability of undergoing mitosis, but remain metabolically active for a long time. Three types of senescence have been reported. (1) Replicative senescence is caused by telomere shortening after a genetically predetermined number of cell divisions in nontransformed cells (Shay and Roninson, 2004). (2) Oncogene-induced senescence possesses the capacity of cells to undergo senescence in the presence of oncogenes (e.g., Ras) (Lee et al., 1999). (3) Premature senescence occurs through exposure of cells to exogenous cytotoxic agents causing DNA damage (Gewirtz, 2014). It is known that cytotoxic response of autophagy to stress and stress-induced senescence evades cell death. However, autophagy can be either a cytoprotective or a cytotoxic response to chemotherapy or radiotherapy. Some information is available regarding a relationship between autophagy and senescence. A cross talk between autophagy and apoptosis has also been established and is discussed elsewhere in this chapter. An increase of autophagic vacuoles and senescence has been observed in the bile duct cells of patients with primary biliary cirrhosis (Sasaki et al., 2010). The generation of autophagic vesicles in dying senescent keratinocytes has been reported (Gosselin et al., 2009), and autophagy markers in senescent endothelial cells have been found. More importantly, Young et al. (2009) reported the upregulation of autophagy-related genes during oncogene-induced senescence, and that inhibition of autophagy delayed the senescence phenotype. Recently, Goehe et al. (2012) reported that treatment of breast cancer cells and colon cancer cells with doxorubicin or camptothecin resulted in both autophagy and senescence. It is concluded that both autophagy and senescence are collaterally induced by chemotherapy in cancer cells. In contrast, interference with ROS generation, ATM activation, and induction of p53 or p21 suppress both autophagy and senescence (Goehe et al., 2012). Both autophagy and senescence signal the immune system the presence of tumor cells that require elimination. In addition, both autophagy and senescence enhance the effect of chemotherapy on cancer cells. Although autophagy accelerates the senescence process by possibly providing an additional source of energy, senescence can occur independently on autophagy. The role of senescence in aging is described elsewhere in this chapter; also, see page 43.

ROLE OF AUTOPHAGY AND CELLULAR SENESCENCE IN AGING It is important to know the interdependence of autophagy and cellular aging. In other words, in order to understand aging it is imperative to find out a variety of molecular events that directly or indirectly are controlled by autophagy. Full capacity of autophagy to


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direct cellular aging as yet is not known, nor are known the genomewide factors that regulate autophagy. Aging and many diseases cannot be prevented, but they can be delayed and some may be cured in the future. Birth, aging, and death are normal, inevitable events; it is known that “there is no birth without death and there is no death without birth.” All existing (living) beings are affected by aging, a fatal and inevitable inherited condition. The role of autophagy in increasing the life span has been extensively studied in various models such as yeast (Matecic et al., 2010), Caenorhabditis elegans (Tóth et al., 2008), and Drosophila (Simonsen et al., 2008). These and other studies indicate that autophagy has antiaging effects, and inhibition of autophagy accelerates aging and negates the longevity promoting effects of caloric restriction (CR) (Rubinsztein et al., 2011; Cheng et al., 2013). Thus, the beneficial effect of CR is mediated, at least in part, by autophagy. This effect is reinforced by the evidence that autophagic gene Bec 1 is required for the longevity effect of CR in C. elegans (Jia and Levine, 2007). This genetic evidence is important. Inhibition of mTOR also extends the life span, which is summarized later. The autophagy process was evolved primarily as a quality control mechanism to protect the cell from damage caused by excess or nonfunctional toxic macromolecules and damaged organelles. Once autophagy is activated, it involves generally the degradation of old, damaged, excess proteins and other cell materials and organelles in order to provide basic, simple molecules for the synthesis and/or repair of macromolecules and organelles. Autophagy is one of the main processes that regulate the rate (speed) of aging. This is expected because of the role of autophagy in age-related diseases such as neurodegeneration (AD and Parkinson’s disease (PD)), cardiovascular diseases (atherosclerosis), and cancer. Autophagy protects against age-related diseases (Nixon, 2013). An example of other diseases connected with the physiological role of autophagy is diabetes; it has been reported that knockout of the essential autophagy gene ATG7 results in diabetic state in mice (Wu et al., 2009). It is known that autophagy is a vital intracellular degradation mechanism that regulates homeostasis at cellular and organism levels. There is a consistent link between diminished or loss of autophagy and accelerated aging and reduced life span. Moreover, overexpression of autophagy gene, ATG5, increases the life span at least of mice (Pyo et al., 2013). It is also known that the process of inevitable aging is associated with the accumulation of dysfunctional, damaged, excess, or old cell macromolecules (proteins) and organelles (mitochondria), which contribute to the age-related diseases. Indeed, one of the most important hallmarks of aging is the accumulation of a variety of molecular damages embodied in malfunctioning organelles (e.g., mitochondria), defective cellular macromolecules (e.g., proteins), and their accumulation, defective enzymes, and/or DNA mutations. These and other cellular damages result in chronic diseases such as cancer, neurodegeneration, Type II diabetes, or increased infection. Changes in the cellular environment (nutrients, cell adhesion, and cell–cell interactions) also play a part by altering kinase signaling pathways. The accumulation of molecular damages is accompanied by the above-mentioned and other diseases, which increase with age. The challenge for the future medicine is to develop strategies to prolong healthy life span by negating the etiology of age-related disorders instead of concentrating exclusively on symptomatic treatments (Madeo et al., 2015). Stimulation of autophagy and its increased flux (within limits) contribute to the extension of healthy life span (without necessarily extending the maximum life span), which can be accomplished



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by nutritional, pharmacologic, and genetic manipulations (Madeo et al., 2015). The level of autophagy induction, for example, can be modulated by adenosine monophosphateactivated protein kinase (AMPK)/ULK1-mediated phosphorylation of mammalian Atg9A (Weerasekara et al., 2014). Autophagy participates in the elimination of cell components mentioned above and reduction of ROS, delaying age-related complications and promoting healthy life span extension. Additionally, it is known that normal or pathologic aging is associated with reduced degradation of dysfunctional cell components by autophagy. In other words, the absence of efficient autophagy (basal, constitutional) contributes to age-related cellular dysfunction (Cuervo, 2008). An interesting question is: what are the changes in autophagy and in the cell during aging? Some fundamental information at the molecular level is available, explaining the aging process. Oxidative damage and incomplete degradation (inefficient housekeeping) of degradable cell components result in the accumulation of deleterious alterations of macromolecules and organelles starting from young to adult stage (Bergamini, 2006). One of the changes is diminished autophagic flux in macrophages from aged mice compared with those from young mice (Stranks et al., 2015). Also, the rate of initiation and maturation of autophagosomes and the efficiency of autophagosome–lysosome fusion decline with age (Rajawat et al., 2009). Additionally, damaged proteins and organelles accumulate in aged organs. As mentioned earlier, autophagy protects the cell against the accumulation of cellular waste products during aging. However, autophagy efficiency declines during aging, which results in the increased accumulation of dysfunctional cell organelles and aberrant cellular materials, which accelerates aging process. Accumulated evidence indicates that degradation by autophagy has a crucial role in the prevention of age-related degeneration and increased life span. Dietary restriction-mediated life span extension is well established. It is also known that autophagy plays an essential role in the antiaging mechanism of CR. As an example, reduced supply of amino acid methionine enhances life span across species, including mammals. Methionine restriction limits the availability of the amino acid, resulting in longevity via autophagy. This role of autophagy becomes evident by the evidence that single deletion of several genes (ATG5, ATG7, or ATG8) required for autophagy abolishes the longevity enhancing capacity of methionine restriction in yeast S. cerevisiae (Ruckenstuhl et al., 2014). Methionine restriction inhibits ROS overproduction and aging associated mortality by both apoptosis and necrosis. Autophagy-mediated vacuolar acidification is essential for the antiaging effect of methionine restriction (Ruckenstuhl et al., 2014). Another effect of methionine restriction that indirectly supports longevity was reported by Sanz et al. (2006). They indicated that such restriction decreases mitochondrial oxygen radical generation and leak as well as oxidative damage to mitochondrial DNA and proteins.

Role of mTOR mTOR is a serine threonine protein kinase present in all eukaryotic organisms. In mammals, mTOR exists in two distinct complexes, termed mTORC1 and mTORC2. Each of these two complexes has distinct protein components, although both share the catalytic mTOR subunit, as well as mLST8 (mammalian lethal with SEC13 protein 8).


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The inhibition of mTOR extends life span in various model systems. Deletion of the mTOR gene in yeast results in an increase in replicative life span that cannot be further extended by nutrient restriction (Kaeberlein et al., 2005). Also, mTOR plays a role in regulating mammalian life span. Treatment of mice with rapamycin (a pharmacological inhibitor of mTOR) results in an extension of life span (Miller et al., 2011). A recent genetic model consisting of mice heterozygous for deletion of mTOR also demonstrated life span extension only in female mice (Lamming et al., 2012). More recently, Wu et al. (2013) provided evidence that reduced mTOR activity produced a marked increase in overall life span in female mice. It is concluded that tissue aging is governed by interconnected but separate regulatory control mechanisms, and the increase in the life span by inhibiting mTOR is tissue specific. Response of mTOR and autophagy to dietary restriction is discussed below.

Response by mTOR and Autophagy to Dietary Restriction Some of the major autophagy-related factors that influence aging are summarized here. One of the main factors associated with life span and aging is mTOR. mTOR regulates a number of processes that are involved in the longevity response to dietary restriction. It is known that limited food intake without malnutrition increases the life span in organisms ranging from yeast to humans. Dietary restriction increases life span, at least in part, by reducing the activities of pathways involved in growth and nutrient processing, including the mTOR pathway. The downregulation of the mTOR pathway plays an important role in the longevity response to food limitation by eliciting autophagy. It has been reported that dietary restriction and mTOR inhibition produce an autophagic phenotype, and that inhibition of genes required for autophagy prevents dietary restriction and mTOR inhibition from extending life span of C. elegans (Hansen et al., 2008). According to these authors autophagy alone is not only insufficient but also unnecessary for life span extension. Inhibition of protein synthesis in an otherwise well-fed C. elegans results in life span extension in the absence of autophagy. However, autophagy is required for longevity pathways that are integrated with and regulated by environmental signals and pathways such as the insulin/IGF-1. The transcription factor DAF-16-FOXO (controls gene expression) is required to program the cells to recycle the raw materials into the cell-protective longevity proteins in order for life span to be increased (Hansen et al., 2008). Autophagy does provide raw materials for the synthesis of macromolecules. Autophagy also requires PHA-4/FOXO (a life extension protein) that regulates gene expression. Changes in gene expression are required for dietary restriction to stimulate autophagy. Is it possible that nonautophagic cell death contributes to the longevity induced by dietary restriction (Hansen et al., 2008)?

Role of Sirtuins Role of Sirtuins in the regulation of aging has been observed in organisms ranging from yeast to mammals (Ghosh, 2008). Sirtuins are homologs of yeast Sir2 (silent information regulator 2) histone deacetylase (HDAC), a gene that regulates the life span of budding yeast (Sinclair et al., 1998). Mammalian seven Sirtuins (SIRT-7) have important functions in the regulation of metabolism, growth and differentiation, inflammation, cellular survival,



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senescence, and life span extension (Michan and Sinclair, 2007). Also, SIRT 1 plays a direct role in the regulation of autophagocytosis (Lee et al., 2008). SIRT 1, additionally, is associated with the Fox0 and p53 signaling pathways that are stress resistance and longevity mediators (Salminen and Kaarniranta, 2009). These pathways regulate both degradation by autophagy and life span extension. In fact, SIRT 1 is involved not only in the degradation by autophagy but also in the stimulation of autophagosome formation, enhancing the cellular cleansing capacity, ensuring that the waste products do not accumulate as the cell ages (Salminen and Kaarniranta, 2009).

Role of Stem Cells Considerable amount of evidence promoting the advantages of using stem cells for compensating damaged or lost cells or organs is available (Hayat, 2011–2015). However, degenerative alterations in tissue-specific stem cells and stem cell niches are thought to occur during aging of the person (Oh et al., 2014). According to this concept, various types of stem cells are unable to continue replenishing tissues of an aging organism with functional differentiated cells capable of maintaining the original function. This problem arises because, in part, the number of stem cells is much lower in older persons than that in younger individuals. This results not only in the diminished cell replacement but also in the inefficient removal of damaged cell components by autophagy. Generally, clearance of misfolded proteins slows with age. Genetic error accumulations are not uncommon regardless of the age. This means that aging may not cause comparatively more cellular damage but the efficient removal of cellular damage does become a problem. Transplantation of stem cells can be tried, but its therapeutic use has its own limitations. One of the problems is that the new differentiated cells may have different life spans even though they origin from the same type of stem cells (Oh et al., 2014). Advantages and limitations of stem cell technology are described in detail elsewhere (Hayat, 2011–2015).

Role of Cellular Senescence Cellular senescence is defined as an irreversible arrest of cell proliferation that occurs when cells are exposed to potentially oncogenic stress to suppress the development of cancer. It is irreversible because no known physiological stimuli can activate senescent cells to enter the cell cycle (Campisi, 2013). Therefore, cellular senescence is an effective barrier to the development of malignant tumorigenesis. However, inactivation of certain tumor genes can cause senescent cells to proliferate (Beausejour et al., 2003). Although specific markers for senescence are not known, semispecific detection methods, including high levels of p16INK4A, p21, macroH2A, IL-6, phosphorylated p38 MAPK, DSBs, and senescence-associated β-galactosidase activity, are available (van Deursen, 2013). Senescence is a highly dynamic, multistep process, during which its properties evolve and diversify (De Cecco et al., 2013). Senescent cells show changes in chromatin organization and gene expression and promote tissue repair or regeneration in the presence of injury (Campisi, 2013). Senescence is also involved in lysosome-mediated processing of chromatin (Ivanov et al., 2013) and accumulates at sites of tissue injury and remodeling (Jeyapalan et al., 2007).


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There is a link between cellular senescence and aging. Senescent cells accumulate in tissues of humans, primates, and rodents (Lawless et al., 2010). With reference to aging and age-related diseases, senescent cells secrete proinflammatory cytokines and other materials that directly or indirectly promote chronic inflammation (Chung et al., 2009; Davalos et al., 2010; Campisi et al., 2011). Inflammation results in a variety of diseases, including virtually every major age-related disease, both degenerative and hypoplastic (Franceschi, 2007; Chung et al., 2009). Cells with senescent cell properties are found in the affected tissues of patients with age-related diseases (osteoarthritis, pulmonary fibrosis, atherosclerosis, AD) (Campisi, 2013; Naylor et al., 2013). Considering almost opposite usual functions of senescence cells, they can be either beneficial or deleterious, depending on the physiological context. Several studies have suggested that senescent cells are a therapeutic target for aging and age-related disorders; also, see page 39.

Effect of Aging on Skeletal Muscle Aging is associated with the progressive decline in skeletal muscle mass, strength, and function, collectively called sarcopenia. The age-related decrease in physical activity contributes to the manifestation of sarcopenia and its related disorders. Sarcopenia specifically contributes to the development of insulin resistance type 2 diabetes and cardiovascular diseases. Declining activity levels lead to increased mortality. Therefore, therapeutic strategies are needed to at least delay the onset of sarcopenia. Since proteins are the main functional molecules and constitute the predominant nonfluid lean mass, the age-related disorders mentioned above result from the impairment in overall skeletal muscle protein homeostasis (the balance between protein synthesis and protein degradation) (Irving et al., 2011). Failure to degrade damaged or abnormal proteins and replacing them with newly synthesized proteins contribute to age-related decline in muscle mass and quality of muscle proteins. Exercise represents a potent stimulus for muscle protein synthesis. Undernutrition due to age-related anorexia has been implicated as a potential contributing factor for the development of sarcopenia, and thus protein requirements increase with age. GaffneyStomberg et al. (2009) recommend an increase in protein from 0.8 to 1.2 g/kg. However, clinical investigators in this regard have produced conflicting results in elderly patients. The functions of proteins are determined both by their quality and quantity. Thus, removal of defective or damaged proteins by controlled autophagy and ubiquitin-proteasome pathway mechanisms is critical for maintaining both their concentration and quality. Signaling occurs between autophagy and proteasome pathways and attachment of a single ubiquitin is sufficient to target a protein for degradation through autophagy (Kim et al., 2008). It is also critical to maintain optimal quantitative balance by synthesizing new proteins. It is relevant to point out that muscle strength declines disproportionate to the decline in their mass, indicating that protein quality also declines with age. A progressive decline in muscle protein synthesis as well as in its degradation occurs with age. A specific example is the progressive decline in protein synthesis in mitochondria with age (Irving et al., 2011). Such a decline adversely affects ATP synthesis that controls both synthesis and degradation of proteins.



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Role of Autophagy in Heart Disease Autophagy impairment is associated with the pathophysiology of aging, and reduced autophagy results in premature aging and shortened life span. In contrast, autophagy induction can prolong life span. Damaged proteins and organelles accumulate in aged organs. If these cell components are not removed or repaired, their accumulation will lead to age-related diseases. For example, heart failure is an age-related disease, the incidence of which increases with age. Autophagy activity of the heart decreases during aging. Yamaguchi and Otsu (2012) report that cardiac-specific autophagy-deficient mice begin to die after the age of 6 months, with a significant increase in the left ventricular dimension and a decrease in the fractional shortening of the left ventricular compared with that in the control mice. This evidence indicates that continuous constitutive autophagy during aging has a crucial role in maintaining cardiac structure and function. Another example is the diminished autophagic flux in macrophages from aged mice compared with that in the young mice (Stranks et al., 2015). These and other studies partly answer the question: What are the changes in autophagy and in the cell during aging? Role of autophagy in heart disease is discussed in more detail later in this chapter.

Role of Autophagy in Huntington’s Disease Defects in autophagy are implicated in Huntington’s disease (HD) in which polyglutamine-expanded huntingtin (polyQ-htt) is predominantly cleared by autophagy. In neurons, autophagosomes form constitutively at the axon tip and undergo robust retrograde axonal transport toward the cell body (Wong and Holzbaur, 2014). Both huntingtin (htt) and its adaptor protein huntingtin-associated protein-1 (HAP1) copurify and colocalize with autophagosomes in neurons (Wong and Holzbaur, 2014). Defective clearance of both polyQ-htt aggregates and dysfunctional mitochondria by neuronal autophagosomes contribute to neurodegeneration and cell death in HD.

Role of Autophagy in Alzheimer’s Disease An interesting example of the effect of extreme environmental stress on the development of Alzheimer’s disease (AD) in mice was reported by Park et al. (2015). Stress is one of the environmental (exogenous) factors that directly or indirectly contribute to some age-related human diseases. Recently, it was reported that stress can increase the production of amyloid-β (Aβ) that is commonly present in the brain, including mouse brain (Park et al., 2015). They obtained this information by restricting mice to induce acute stress. They also obtained increased Aβ levels by treating mice with primary neuronal cells and human neuroblastoma cells with corticotrophin releasing factor (CRF); this hormone mediates stress in mice and humans.

Role of Autophagy in Macular Degeneration The role of autophagy in another age-related disorder, macular degeneration, has been reported (Viiri et al., 2010). Although this disorder does not shorten life span, it can ultimately lead to visual loss. This disease affects the macula located in the central area of the


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retina. The degeneration of the macular retinal pigment epithelial (RPE) cells is characteristic of this disorder (Kaarniranta et al., 2009). Normally, RPE cells take care of the health of rods and cones. Chronic oxidative stress and inflammation are key factors causing RPE degeneration and promotion of macular degeneration (Beatty et al., 2000). The accumulation of lysosomal lipofuscin indicates defective clearance of this complex protein in aged RPE cells (Kaarniranta et al., 2009). Increased levels of autophagic markers and decreased lysosomal activity in the RPE cells has been reported (Wang et al., 2009).

ROLE OF AUTOPHAGY IN VIRAL DEFENSE AND REPLICATION Viruses and other pathogens induce dramatic changes in the intracellular environment. Infected cells activate certain defense pathways to combat the pathogen. On the other hand, pathogens interfere with defense processes and utilize cellular supplies for pathogen propagation. Autophagy, for example, plays an antiviral role against the mammalian vesicular stomatitis virus, and PI3K-Akt signaling pathway is involved in this defense process (Shelly et al., 2009). Many virus types, including herpes simplex virus 1 and Sindbus virus, have been observed inside autophagic compartments for degradation (Orvedahl et al., 2007). Autophagy is an essential component of Drosophila immunity against vesicular stomatitis virus (Shelly et al., 2009). Recently, an interesting role of RNAse L system and autophagy in the suppression or replication of encephalomyocarditis virus or vesicular stomatitis virus was reported (Chakrabarti et al., 2012). At a low multiplicity of infection, induction of autophagy by RNAse L suppresses virus replication, but in subsequent rounds of infection, autophagy promotes viral replication. RNAse is a virus-activated host RNAse pathway that disposes of or processes viral and cellular single-stranded RNAs. However, it has not been established if autophagy itself is sufficient to control viral replication in all cases; the participation of other cell death phenomena in this defense process cannot be disregarded. On the other hand, autophagy, for example, is actively involved in the influenza A virus replication (Zhou et al., 2009). Mouse hepatitis virus and polio virus sabotage the components of the mammalian autophagy systems, which normally is important in innate immune defense against intracellular pathogens. In other words, autophagic machinery (which normally would function to eliminate virus) may promote viral assembly (Jackson et al., 2005). However, Zhao et al. (2007) indicate that mouse hepatitis virus replication does not require autophagy gene Atg5. The survival of HIV depends on its ability to exploit host cell machinery for replication and dissemination, to circumvent cellular defense mechanisms, or to use them for its replication. Autophagy plays a dual role in HIV-1 infection and disease progression. Direct effects of HIV on autophagy include the subversion of autophagy in HIV-infected cells and the induction of hyperautophagy in bystander CD4+ T cells. HIV proteins modulate autophagy to maximize virus production (Killian, 2012). Alternatively, HIV-1 protein also disrupts autophagy in uninfected cells and thus contributes to the death of CD4+ T cells and viral pathogenesis. It has also been reported that HIV-1 downregulates autophagy regulatory factors, reducing both basal autophagy and the number of autophagosomes per cell (Blanchet et al., 2010). The HIV negative elongation factor (Nef) protein protects HIV from degradation by inhibiting autophagosome maturation (Kyei et al., 2009). It has been shown that foot and mouth


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disease virus induces autophagosomes during cell entry to facilitate infection but does not provide membranes for replication (Berrym et al., 2012). Another example of a virus that uses a component of the autophagy to replicate itself is hepatitis C virus (HCV) (Sir et al., 2012). HCV perturbs the autophagic pathway to induce the accumulation of autophagosomes in cells (via PI3KCIII-independent pathway) and uses autophagosomal membranes for its RNA replication. Other positive-strand RNA viruses (poliovirus, dengue virus, rhinoviruses, and nidoviruses) also use the membrane of autophagic vacuoles for their RNA replication (Sir and Ou, 2010). Suppression of the LC3 and Atg7 reduces the HCV RNA replication level; these two proteins are critical for autophagosome formation. There is still controversy regarding the contrasting roles of autophagy in pathogen invasion; the mechanisms governing activation of autophagy in response to virus infection require further elucidation.

ROLE OF AUTOPHAGY IN INTRACELLULAR BACTERIAL INFECTION Posttranslation modifications of cell proteins (e.g., ubiquitination) regulate the intracellular trafficking of pathogens. Ubiquitination involves the addition of ubiquitin to the lysine residues of target proteins, resulting in endocytosis and sorting events (Railborg and Stenmark, 2009). Several strategies have been developed by pathogenic bacteria to interfere with the ubiquitination of the host and thus to achieve successful infection. Some types of bacteria act directly on the ubiquitination pathway by mimicking host cell proteins, while others (e.g., Escherichia coli, Shigella flexneri) act indirectly by expressing or interfering with the host ubiquitination pathway. Another defense by the cell against bacterial infection is through autophagy that is described below. Autophagy serves as a double-edged sword; on the one hand it eliminates some pathogens and bacterial toxins, while on the other hand, some pathogens can evade or exploit autophagy for survival and replication in a host. Recently, it has become clear that the interaction between autophagy and intracellular pathogens is highly complex. The components of the autophagy machinery also play roles in infection in a process different from the canonical autophagy pathway (formation of a double-membrane autophagosome and the involvement of more than 35 autophagy-related proteins, including LC3 mammalian autophagy marker). There is an alternative autophagy pathway that is relevant to infection. For example, a subset of autophagy components can lead to LC3 conjugation onto phagosomes (Cemma and Brumell, 2012). In other words, the process of LC3-associated phagocytosis (LAP) results in the degradation of the cargo by promoting phagosome fusion with lysosomes. It is likely that both the LAP process and the canonical system operate simultaneously or selectively as host defenses against infection. Examples of bacteria the growth of which is suppressed by autophagy are: E. coli (Cooney et al., 2010), Salmonella typhimurium (Perrin et al., 2004), Streptococcus pyogenes (Virgin and Levine, 2009) and Mycobacterium tuberculosis (Randow, 2011); examples of bacteria that exploit autophagy for replication are: Staphylococcus aureus, Legionella pneumophila, and Yersinia pseudotuberculosis; examples of bacteria that can evade targeting by autophagy/LAP are: Listeria monocytogenes (Randow, 2011), S. flexneri (Virgin and Levine, 2009), and Burkholderia pseudomallei.


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ROLE OF AUTOPHAGY IN HEART DISEASE Heart failure is one of the leading causes of morbidity and mortality in industrialized countries. Myocardial stress due to injury, valvular heart disease, or prolonged hypertension induces pathological hypertrophy, which contributes to the development of heart failure and sudden cardiac death (Ucar et al., 2012). It has been reported that autophagy is an adaptive mechanism to protect the heart from hemodynamic stress. In fact, autophagy plays a crucial role in the maintenance of cardiac geometry and contractile function (Nemchenko et al., 2011). Cardiac-specific loss of autophagy causes cardiomyopathy. Impaired autophagy has been found in a number of heart diseases, including ischemia/reperfusion injury. Excessive and uncontrolled autophagy leads to loss of functional proteins, depletion of essential organic molecules, oxidative stress, loss of ATP, collapse of cellular catabolic machinery, and ultimately death of cells in the heart. Autophagic elimination of damaged organelles, especially mitochondria, is crucial for proper heart function, whereas exaggerated autophagic activity may foster heart failure. Therefore, a delicate balance of autophagy maintains cardiac homeostasis, whereas the imbalance leads to the progression of heart failure. A consensus on whether autophagy is cardioprotective or leads to hypertrophy and heart failure is lacking. In any case, autophagy is an important process in the heart. Various studies indicate that autophagy has a dual role in the heart where it can protect against or contribute to cell death depending on the stimulus. It occurs at low basal levels under normal conditions and is important for the turnover of organelles. Autophagy is upregulated in the heart in response to stress such as ischemia/reperfusion. Studies of ischemia/reperfusion injury indicate that ROS and mitochondria are critical targets of injury, for opening of the mitochondrial permeability transition pore culminates in cell death. However, Sciarretta et al. (2011) indicate that autophagy is beneficial during ischemia but harmful during reperfusion. It has been shown that mitophagy mediated by Parkin is essential for cardioprotection (Huang et al., 2011). The sequestration of damaged mitochondria depends on Parkin, which averts the propagation of mitochondria-induced ROS release and cell death. The implication is that mitochondrial depolarization and removal through mitophagy is cardioprotective. The sequestration of damaged cell materials into autophagosomes is essential for cardioprotection. Increased number of autophagosomes is a prominent feature in many cardiovascular diseases such as cardiac hypertrophy and heart failure (Zhu et al., 2007). Recently, Gottlieb and Mentzer (2013) have ably reconciled contradictory findings and concluded that the preponderance of evidence leans toward a beneficial role of autophagy in the heart under most conditions. Recently, it was reported that autophagy plays a role in the onset and progression of alcoholic cardiopathy (Guo and Ren, 2012). AMPK plays a role in autophagic regulation and subsequent changes in cardiac function following an alcoholic challenge. It is known that AMPK promotes autophagy via inhibition of mTORC1 by phosphorylating the mTORC1associated protein Raptor and tuberous sclerosis complex 2. MicroRNAs (miRNAs) also play a role in cardiomyopathy and heart failure. These endogenous small molecules regulate their target gene expression by posttranscriptional


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regulation of messenger RNA. Recently, it was demonstrated that hypertrophic conditions induced the expression of miR-212/132 family in cardiomyocytes, and both of these molecules regulated cardiac hypertrophy and cardiomyocyte autophagy (Ucar et al., 2012). Cardiac hypertrophy and heart failure in mice can be rescued by using pharmacological inhibitor of miR-132. Inflammation is also implicated in the pathogenesis of heart failure. Some information is available regarding the mechanism responsible for initiating and integrating inflammatory responses within the heart. Mitochondrial DNA plays an important role in inducing and maintaining inflammation in the heart. Mitochondrial DNA that escapes from autophagy cell autonomously leads to TLR 9-mediated inflammatory responses in cardiomyocytes and is capable of inducing myocarditis and dilated cardiomyopathy (Oka et al., 2012). Pressure overload induces the impairment of mitochondrial cristae morphology and functions in the heart. It is known that mitochondria damaged by external hemodynamic stress are degraded by the autophagy/lysosome system in cardiomyocytes (Nakai et al., 2007). It is also known that increased levels of circulating proinflammatory cytokines are associated with disease progression and adverse outcomes in patients with chronic heart failure.

ROLE OF AUTOPHAGY IN NEURODEGENERATIVE DISEASES AD, PD, and HD are the major neurodegenerative conditions causing dementia and movement disorders in the aging population. All three diseases are characterized by the presence of abnormal protein aggregates and neuronal death, although the etiology of AD is distinct from that of PD and HD. It is known that epigenetic dysregulation and transcriptional dysregulation are pathological mechanisms underlying neurological diseases. It is also known that histone deacetylase inhibitor (HDACI), 4b, preferentially targets HDAC1 and HDAC3 ameliorating, for example, HD (Jia et al., 2012). HDAC are enzymes that remove acetyl groups from lysine amino acids on a histone. Several studies have identified HDACIs (4b) as candidate drugs for the treatment of neurodegenerative diseases, including HD. Familial AD mutations increase the amyloidogenicity of the AB peptide, placing disruption of amyloid precursor protein (APP) metabolism and AB production at the center of AD pathogenesis (Pickford et al., 2008). An increase in the production of both APP and AB and a decrease in the degradation of APP contribute to AD. PD is a progressive neurodegenerative disorder caused by the interaction of genetic and environmental factors. It is characterized by the loss of dopaminergic neurons. The available evidence indicates that mitochondrial dysfunction, environmental toxins, oxidative stress, and abnormal accumulation of cytoplasmic proteinaceous materials can contribute to disease pathogenesis. These proteins tend to aggregate within Lewy bodies. The loss of dopaminergic neurons in the substantia nigra may be partly due to the accumulation of aggregated or misfolded proteins or mitochondrial dysfunction. Prevention of such accumulation or degeneration of dysfunctional mitochondria might prevent the occurrence of apoptosis. Mutations in the DJ-1 oncogene are also implicated in the pathogenesis of this


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disease. This oncogene is neuroprotective by activating the ERK1/2 pathway and suppressing mTOR in the dopaminergic neurons, leading to enhanced autophagy. One of the major constituents of Lewy bodies is a protein called alpha-synuclein. This protein is likely to be a toxic mediator of pathology in PD because wild-type alpha-synuclein gene duplications, which increase its expression levels, cause rare cases of autosomal dominant PD (Winslow and Rubinsztein, 2011). Overexpression of alpha-synuclein increases mutant huntingtin aggregation. Mutant huntingtin is an autophagy substrate, and its level increases when autophagy is compromised. Even physiological levels of this protein negatively regulate autophagy. HD is characterized by the accumulation of mutant huntingtin (the protein product of the IT15 gene) in intraneuronal inclusions primarily in the brain but also peripherally. The increase is caused by the appearance of cytoplasmic (neutrophil) and nuclear aggregates of mutant huntingtin, and selective cell death in the striatum and cortex (DiFiglia et al., 1997). HD is recognized as a toxic gain-of-function disease, where the expansion of the polyQ stretch within huntingtin confers new deleterious functions on the protein. Loss of normal huntiungtin function is thought to be responsible for HD. Amyotrophic lateral sclerosis (ALS) is the fourth common neurodegenerative disease, which is characterized by progressive loss of upper and motor neurons. The following genes and proteins have been reported to be involved in familial ALS: superoxide dismutase 1 (SOD1), als2, TAR DNA-binding protein 43 kDa, fused in sarcoma, and optineurin (Da Cruz and Cleveland, 2011). Accumulation of ubiquitinated inclusions containing these gene products is a common feature in most familial ALS models and is also a pathologic hallmark of sporadic ALS. Failure to eliminate detrimental proteins is linked to pathogenesis of both familial and sporadic types of ALS. Dysfunction of the 26S proteasome in motor neurons is sufficient to induce cytopathological phenotypes of ALS (Tashiro et al., 2012). This evidence indicates that dysfunction of UPS primarily contributes to the pathogenesis of sporadic ALS. In other words, proteasomes, but not autophagy fundamentally governs the development of ALS in which TDP-43 and FUS proteinopathy plays a crucial role (Tashiro et al., 2012). The role of autophagy in the AD, PD, and HD is further elaborated below. Loss of autophagy-related genes results in neurodegeneration and abnormal protein accumulation. Autophagy is important to avoid or at least delay the development of age-related diseases such as neurodegeneration and cancer. In fact, autophagy is an essential pathway in postmitotic cells, such as neurons, cells that are particularly susceptible to the accumulation of defective proteins and organelles. Neuron-specific disruption of autophagy results in neurodegenerative diseases, including AD, PD, HD, ALS, and prion. Tissue-specific genetic manipulation of autophagy of the brain causes neuronal accumulation of misfolded proteins and an accelerated development of neurodegeneration. One of the prominent features of AD is the accumulation of autophagic vacuoles in neurons suggesting dysfunction in this degradation pathway. Autophagy is normally efficient in the brain as reflected by the low number of brain autophagic vacuoles at any given moment (Nixon and Yang, 2011). In contrast, brains of AD patients exhibit prominent accumulation of such vacuoles in association with dystrophic neuritis and deformed synaptic membranes (Yu et al., 2005).


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The majority of PD is idiopathic with no clear etiology. The loss of dopaminergic neurons in the substantial nigra may be partly due to the accumulation of aggregated or misfolded proteins or mitochondrial dysfunction. Prevention of such accumulations or degradation of dysfunctional mitochondria might prevent the occurrence of apoptosis. Mutations in the DJ-1 oncogene are also implicated in the pathogenesis of this disease. DJ-1 is neuroprotected by activating the ERL1/2 pathway and suppressing mTOR in the dopaminergic neurons, leading to enhanced autophagy. Upregulation of autophagy has the potential to be a therapeutic strategy for disorders. This genetic method for autophagy upregulation is mTORindependent. The development of genetic-based therapeutic strategies aimed at stimulating the autophagic clearance of aggregated proteins can be used in both the treatment of neurodegenerative diseases and in life span extension (Zhang et al., 2010). Several studies have identified HDACIs (4b) as candidate drugs for the treatment of neurological diseases, including HD.

CROSS TALK BETWEEN AUTOPHAGY AND APOPTOSIS The cross talk between autophagy and apoptosis is exceedingly complex, and various aspects of this phenomenon are still being understood. A brief introduction to the apoptosis pathway is in order. The significant functions of apoptosis (type 1 programmed cell death) are embodied in its maintenance of organism homeostasis and metabolic balance and organ development. Morphological changes and death in apoptotic cells are caused by caspases, which cleave more than 400 proteins. The earliest recognized morphological changes in apoptosis involve condensation of cytoplasm and chromatin, DNA fragmentation, and cell shrinkage. The plasma membrane convolutes or blebs in a florid manner, producing fragments of a cell (apoptotic bodies). The fragments are membrane bound and contain nuclear parts. The apoptotic bodies are rapidly taken up by nearby cells and degraded within their lysosomes. There are two major established signaling pathways that result in apoptosis. In the extrinsic pathway, apoptosis is mediated by death receptors on the cell surface, which belong to the TNF receptor superfamily and are characterized by extracellular cysteine-rich domains and extracellular death domain. In other words, extrinsic pathway is induced by cell death receptor pathways such as TRAIL or FAS ligand. The cell surface receptors form a multiprotein complex called the death-inducing signaling complex. The intrinsic pathway, on the other hand, is mediated by mitochondria in response to apoptotic stimuli, such as DNA damage, irradiation and some other anticancer agents (Zhan et al., 2012), serum deprivation, cytochrome c, SMAC/DIABLO (direct inhibitor of apoptosis-binding protein), AIF (apoptosis-inducing factor that promotes chromatin condensation), and EndoG (endonuclease G facilitates chromatin condensation). Cytochrome c binds to and activates Apaf-1 protein in the cytoplasm. This induces the formation of the apoptosome that subsequently recruits the initiator procaspase-9, yielding activated caspase-9 and finally mediates the activation of caspase-3 and caspase-7 (Tan et al., 2009). It is apparent that diverse stimuli cause release of mitochondrial proteins to activate the intrinsic apoptosis pathway leading to MOMP and the release of cytochrome c and other


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apoptogenic proteins; MOMP is regulated by the Bcl family of proteins. In summary, in both pathways, activated caspases cleave and activate other downstream cellular substrates as explained above. Under stress conditions, prosurvival and prodeath processes are simultaneously activated and the final outcome depends on the complex cross talk between autophagy and apoptosis. Generally, autophagy functions as an early-induced cytoprotective response, favoring stress adaptation by removing damaged subcellular constituents. It is also known that apoptotic stimuli induce a rapid decrease in the level of the autophagic factor–activating molecule in Beclin 1–regulated autophagy (Ambra 1) (Pagliarini et al., 2012). Such Ambra 1 decrease can be prevented by the simultaneous inhibition of caspases and calpains. Caspases cleave Ambra 1 at the D482 site, while calpains are involved in complete Ambra 1 degradation. Ambra 1 levels are critical for the rate of apoptosis induction. Autophagy can trigger caspase-independent cell death by itself or by inducing caspasedependent apoptosis. Autophagy can protect cells by preventing them from undergoing apoptosis. Autophagy also protects cells from various other apoptotic stimuli. Although the exact mechanism underlying this protection is not known, the role of damaged mitochondrial sequestration has been suggested, which prevents released cytochrome c from being able to form a functional apoptosome in the cytoplasm (Thorburn, 2008). There is a close connection between the autophagic machinery and the apoptosis machinery. Is it possible that there is a simultaneous activation of these two types of death processes? In fact, autophagy is interconnected with apoptosis as the two pathways share key molecular regulators (Eisenberg-Lerner et al., 2009). For example, it has been reported that autophagy regulates neutrophil apoptosis in an inflammatory context-dependent manner and mediates the early proapoptotic effect of TNF-α in neutrophils. Neutrophils are a major subset of circulating leukocytes and play a central role in defense against bacterial and fungal infections. The concept of the presence of cross talk between autophagy and apoptosis is reinforced by indicating that common cellular stresses activate various signaling pathways that regulate both of these two cellular death programs. ROS induce apoptosis and regulate Atg4 that is essential for autophagy induction. In addition, Atg5 promotes both apoptosis and autophagy induction. In addition to Atg5, several other signal transduction pathways (Bcl2 regulator) can illicit both apoptosis and autophagy of these two cell death mechanisms. The transcription factor p53 is also one such molecule. Several recent studies have revealed additional information regarding the molecular mechanisms underlying the cross talk between autophagy and apoptosis. An interesting study of the effect of Ganoderic acid (a natural triterpenoid) on melanoma cells was recently carried out by Hossain et al. (2012). This study indicated that this acid induced an orchestrated autophagic and apoptotic cell death, as well as enhanced immunological responses via increased HLA class II presentation in melanoma cells. In other words this treatment initiated a cross-walk between autophagy and apoptosis as evidenced by increased levels of Beclin 1 and LC3 proteins. Another study investigated the effect of taurine on METH-induced apoptosis and autophagy on PC12 cells and the underlying mechanism (Li et al., 2012). METH, a commonly abused psychostimulant, induces neuronal damage by causing ROS formation, apoptosis, and autophagy. Taurine, in contrast, decreases METH-induced damage via inhibiting


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autophagy, apoptosis, and oxidative stress through the mTOR-dependent pathway. It is known that mTOR is the major negative regulator of autophagy. The cross talk between autophagy and apoptosis is indicated further by the involvement of Beclin 1 in both of these cellular programmed cell death types. Autophagy and apoptosis are two dynamic and opposing (in most cases) processes that must be balanced to regulate cell death and survival. Available evidence clearly indicates that a cross talk between autophagy and apoptosis does exist and that in its presence, the former precedes the latter. Also, autophagy may delay the occurrence of apoptosis. Many studies indicate that cancer cells treated with an anticancer drug induce both autophagy and apoptosis. In addition, normal cells exposed to cancer-causing agents tend to invoke defense by inducing both autophagy and apoptosis. Moreover, cancer cells exposed to anticancer agents induce autophagy, but in the absence of autophagy, these cells develop apoptosis. This concept is confirmed by a recent study by Li et al. (2012) who indicate that oridonin (an anticancer agent) upregulates p21 (an antitumor gene) expression and induces autophagy and apoptosis in human prostate cancer cells, and that autophagy precedes apoptosis, and thus, protecting such treated cells from apoptosis by delaying its onset. To substantiate the above conclusions, several other recently published reports follow. Coregulation of both autophagy and apoptosis using bis-benzimidazole derivatives has been reported (Wang et al., 2012). These compounds are potent antitumor agents. The implication is that autophagy and apoptosis act in synergy to exert tumor cell death. In another study it was shown that low-density lipoprotein receptor-related protein-1 (LRP1) mediates autophagy and apoptosis caused by Helicobacter pylori in the gastric epithelial cell line AZ-521 (Yahiro et al., 2012). This study also proposes that the cell surface receptor, LRP1, mediates vacuolating cytotoxin-induced autophagy and apoptosis; this toxin induces mitochondrial damage leading to apoptosis. In these cells the toxin triggers formation of autophagosomes, followed by autolysosome formation. Recently, it was reported that DAPK induces autophagy in colon cancer cells in response to the treatment with HDACI, while in autophagy-deficient cells, DAPK plays an essential role in committing cells to HDACI-induced apoptosis (Gandesiri et al., 2012). Further evidence supporting the cross talk between autophagy and apoptosis was recently reported by Visagie and Joubert (2011). They demonstrated the induction of these two programmed cell death mechanisms in the adenocarcinoma cell line (MCF-7), which was exposed to 2-methoxyestradiol-bis-sulfamate (2-MeDE2bis MATE), a 2-methoxyestradiol derivative (an anticancer agent). The presence of apoptosis was indicated in this morphological study by growth inhibition, the presence of a mitotic block, membrane blebbing, nuclear fragmentation, and chromatin condensation, which are hallmarks of this type of cell death. Simultaneously, this drug likely inducted autophagy as indicated by showing increased lysosomal staining. Organic compounds have also been used to determine the cross talk between autophagy and apoptosis. A few examples follow. Pterostilbene (a naturally occurring plant product) activates autophagy and apoptosis in lung cancer cells by inhibiting epidermal growth factor receptor and its downstream pathways (Chen et al., 2012b). Gui et al. (2012) used glyphosate (a herbicide linked to PD) for inducing autophagy and apoptosis in PC12 cells and found that Beclin-1 gene was involved in the cross talk between the mechanisms governing the two


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programmed cell death processes. Two plant products, dandelion root extract and quinacvine, mediate autophagy and apoptosis in human pancreatic cancer cells and colon cancer cells, respectively (Ovadje et al., 2012; Mohapatra et al., 2012). Hirsutanol A compound from fungus Chondrostereum inhibits cell proliferation, elevates ROS level, and induces autophagy and apoptosis in breast cancer MCF-7 cells (Yang et al., 2012). A switch from apoptosis to autophagy is not uncommon during chemoresistance by cancer cells. It is known that defective apoptosis is an important mechanism underlying chemoresistance by cancer cells. Such resistance is associated with profound changes in cell death responses and a likely switch from apoptosis to autophagy. This switch involves balancing of the deletion of multiple apoptotic factors by upregulation of the autophagic pathway and collateral sensitivity to the therapeutic agent. Ajabnoor et al. (2012) have reported that reduction of apoptosis occurring in the MCF-7 breast cancer cells upon acquisition of paclitaxel resistance is balanced by upregulation of autophagy as the principal mechanism of cytotoxicity and cell death; this sensitivity is associated with mTOR inhibition. Upregulation of the autophagic pathway gives rise to rapamycin resistance. Also, loss of expression of caspase-7 and caspase-9 is observed in these cells. It is known that cell survival mechanism is driven by Beclin 1-dependent autophagy, while cell death is controlled by caspases-mediated apoptosis. Both of these processes share regulators, such as Bcl2, and influence each other through feedback loops. The question is whether autophagy and apoptosis coexist at the same time at the same stress level. To elucidate the role of regulatory components involved in both autophagy and apoptosis and better understand the cross talk between these two programmed cell death mechanisms, Kapuy et al. (2013) have explored the systems level properties of a network comprising of cross talk between autophagy and apoptosis using a mathematical model. They indicate that a combination of Bcl2-dependent regulation and feedback loops between Beclin 1 and caspases strongly enforces a sequential activation of cellular responses depending upon the intensity and duration of stress levels (transient nutrient starvation and growth factor withdrawal). This study also shows that amplifying loops for caspases activation involving Beclin 1-dependent inhibition of caspases and cleavage of Beclin 1 by caspases not only make the system bistable but also help to switch off autophagy at high stress levels. In other words, autophagy gets activated at lower stress levels, whereas the activation of caspases is restricted to only higher levels of stress. Apparently, autophagy precedes apoptosis at lower stress levels, while at a very high stress level apoptosis is activated instantaneously and autophagy is inactivated. According to this observation, autophagy and apoptosis do not coexist together at the same time at the same stress level. In summary, it is pointed out that a close relationship exists between autophagy and apoptosis and that autophagy and apoptosis are not mutually exclusive pathways. They can act in synergy, can counteract, or even balance each other. Both share many of the same molecular regulators (Bcl2). However, the stress (e.g., nutrient deficiency, growth factor withdrawal) level tends to affect autophagy and apoptosis differently from each other, resulting in balancing each other. Thus, in a clinical setting it is difficult to predict the outcome of inhibition or activation of one process programmed cell death (autophagy) without considering that of the other programmed cell death (apoptosis) (Eisenberg-Lerner et al., 2009). Because autophagy is involved not only in cell death but also mostly in cell survival,


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but apoptosis leads only to cell death, an understanding of the critical balance between these two types of cellular processes is required to design anticancer therapeutics. The dual role of autophagy depends on the context and the stimuli. It has even been proposed that not only autophagy and apoptosis but also programmed necrosis may jointly decide the fate of cells of malignant neoplasms (Ouyang et al., 2012). Further investigations are required to understand the interplay between these two important cellular processes.

AUTOPHAGY AND UBIQUITINATION Ubiquitin is a small (76-amino acid) protein that is highly conserved and widely expressed in all eukaryotic cells. Ubiquitination involves one or more covalent additions to the lysine residues of target proteins. Ubiquitination is a reversible process due to the presence of deubiquitinating enzymes (DUBs) that can cleave ubiquitin from modified proteins. Posttranslational modification of cell proteins, including ubiquitination, is involved in the regulation of both membrane trafficking and protein degradation. Ubiquitination is also implicated in the autophagy pathway (Kirkin et al., 2009).

AUTOPHAGY AND NECROPTOSIS Necroptosis (type 3 programmed cell death) is one of the three basic cell death pathways. The functions of necroptosis include the regulation of normal embryonic development, T-cell proliferation, and chronic intestinal inflammation. The molecular mechanisms underlying TNF α -induced necroptosis and autophagy have been deciphered, which are elaborated below. Necrostatin-1 (Nec-1), targeting serine-threonine kinase receptor-interacting protein-1 (RIP1), is a specific inhibitor of necroptosis which is dependent on RIP1/3 complex activation (Degterev et al., 2008). Tumor necrosis factor alpha (TNFα) induces necroptosis and autophagy. It was recently found that TNFα administration caused mitochondrial dysfunction and ROS production (Ye et al., 2012). Mitochondrial dysfunction led to necroptosis and autophagy in murine fibrosarcoma L929 cells. Nec-1 represses, whereas pan-caspase inhibitor z-VAD-fmk (z-VAD) increases RIP1 expression. This increase, in turn, enhances TNFαinduced mitochondrial dysfunction and ROS production. It has also been shown that TNFα administration and zVAD induce cytochrome c release from mitochondria, whereas Nec-1 blocks this release (Ye et al., 2012). In addition to apoptosis, necroptosis and autophagy are implicated in controlling both innate and adaptive immune functions. It has been demonstrated that the death of cells following ligation of death receptors (a subfamily of cell surface molecules related to TNF receptor 1) is not exclusively the domain of caspase-dependent apoptosis (Lu and Walsh, 2012). In these cells, cell death occurs via necroptosis.


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MITOCHONDRIAL FUSION AND FISSION Mitochondria form highly dynamic organelles that are continuously fusing and dividing to control their size, number, and morphology. The balance between these two processes regulates their shape. Loss of mitochondrial fusion generates many small mitochondria, while their inability to divide results in elongated mitochondria in most cells (Kageyama et al., 2012). The central components that mediate mitochondrial dynamics are three conserved dynamin-related GTPases (Kageyama et al., 2011). In mammals, mitochondrial fusion is mediated by mitofusion 1 and 2, and Opal, which are located in the outer and inner membranes, respectively. Mitochondrial division is mediated by Drpl that is mainly located in the cytosol. Drpl is recruited to the mitochondrial surface by other outer membrane proteins (e.g., Mff, MiD49) (Otera et al., 2010; Palmer et al., 2011). The importance of information on functions of Mfn2 and Opal becomes evident considering that mutations in these genes cause neurodegenerative disorders. In other words alternations in mitochondrial fusion and fission are associated with neurodevelopmental abnormalities. Mitochondria are highly dynamic cellular organelles involved in a wide variety of physiological functions, including ATP production, apoptosis, calcium and iron homeostasis, aging, lipid metabolism, and the production of ROS. Although mitochondria are generally thought to be morphologically static, they alter their morphology continuously in response to various cellular signals; this phenomenon is termed mitochondrial dynamics (Zungu et al., 2011). These alterations involve mitochondrial division (fission) and the merging of individual mitochondria (fusion). Contact site between the inner and outer mitochondrial membranes consists of components of the mitochondrial permeability transition pore, which serves as the site for fission and fusion (Reichert and Neupert, 2004). Under certain starvation conditions (e.g., amino acid depletion), mitochondria may escape autophagosomal degradation through extensive fusion. Such mitochondrial fusion under starvation conditions provides enough ATP necessary for cell survival. Downregulation of the mitochondrial fission protein Drpl is considered to be responsible for the fusion (Rambold et al., 2011a). The process of fusion tends to result in the interconnected mitochondrial network through their elongation. As expected, pharmacological and genetic inhibition of mTOR leads to increased mitochondrial fusion. It is known that mTOR controls mitochondrial fusion. However, other signaling pathways (e.g., AMPK and PKA) may also be involved in starvation-induced mitochondrial fusion during starvation (Rambold et al., 2011b).

SELECTIVE AUTOPHAGY Autophagy is a more selective process than originally anticipated. Autophagy exhibits significant versatility in its selectivity to degrade cell components. This type of autophagy distinguishes cargo to be degraded from its functional counterpart. Some information on the molecular basis of selective autophagy is available. Selective (macro) autophagy includes three critical stages (Okamoto, 2014): (1) signaling from degradation cues induces downstream events specific for a particular target; (2) regulation of important recognized molecules that tag the targets as the disposable cargo; and (3) assembly of core autophagy-related proteins to sequester the specific cargo.


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A selective autophagy receptor/adapter protein is required to bind specifically to a cargo and dock onto the forming autophagosomes (phagophore), facilitating autophagic sequesteration and degradation of the cargo. Such receptors engage the substrate with the autophagy machinery; examples are Atg32 for mitophagy and Atg 19 for the cytoplasm to vacuole targeting pathway. Autophagosomes are specifically generated around the cargo to be degraded via recognition by autophagy receptors, including p62/SQSTM1, NBR1, OPTN, and BN1P3L (Nix), which act as bridges between LC3 on the autophagosome membrane and cargo marked for degradation (Stolz et al., 2014). Autophagy receptors/adaptors provide mechanistic insight into selective autophagy process. Autophagy selectivity is accomplished via the LC3-interacting region (L1R) motif, which ensures the targeting of autophagy receptors to LC3 (or other Atg8 family proteins) anchored in the phagophore membrane (Birgisdottir et al., 2013). Specific autophagy receptors sequester specific cargo into autophagosomes. L1R-containing proteins include cargo receptors, members of the basal autophagy apparatus, proteins associated with vesicles and their transport, Rab/GTPase-associated proteins (GAPs), and the specific signaling proteins, each of which is degraded by selective autophagy (Birgisdottir et al., 2013). These proteins interact with Atg8 proteins, resulting in the recruitment of cargo to the inner surface of the phagophore and for the recruitment of effector proteins to the outer phagosomal membrane where these effectors mediate transport and maturation of autophagosomes. The first selective autophagy receptor to be identified was p62 (SQSTM1) (Bjorkoy et al., 2005). The human p62 protein is 440 amino acids long and contains an N-terminal PB1 domain followed by a zz-type zinc finger domain, nuclear localization signals, unclear export signal, LC3- interacting region, K1R motifs, and a terminal Ub-associated domain (Johansen and Lemark, 2011). p62 harbors active nuclear import and export signals and shuttles between the nucleus and cytoplasm. It is known that p62 acts as a scaffold protein in signaling pathways involving NF-KB and accumulates in ubiquitin-containing protein inclusions in many protein-aggregation diseases (e.g., AD) (Zatloukal et al., 2002). It is also known that p62 is both a selective autophagy substrate and a cargo receptor for autophagic degradation of ubiquitinated protein aggregates (Bjorkoy et al., 2005). p62, in addition, binds both ubiquitin and LC3, and is removed by autophagy; autophagy blockage results in the failure to degrade p62 that leads to protein aggregation (Komatsu and Ichimura, 2010b). p62 recruits autophagy adapter autophagy-linked FYE (ALFY) protein (encoded by the gene located on chromosome 4q21) that in turn recruits the core autophagy machinery ULK1 complex and Vps34 complex (Lin et al., 2013). Both bring the cargo in contact with the core autophagy machinery, allowing the formation of the autophagosomal membrane around the cargo, allowing its sequestration (Isakson et al., 2013). A direct interaction between these adaptors and the autophagosomal marker protein LC3 is required for specific recognition of substrates and efficient selective autophagy (Johansen and Lemark, 2011). (The best described adaptor protein is yeast Atg11 involved in the Ctv pathway.) The cargo consists of ubiquitinated protein aggregates. ALFY is mainly located in the nucleus under normal conditions but is transferred to the cytoplasm as protein aggregates upon cellular stress. These receptors do not seem to be involved in the bulk degradative autophagy. NBR1 (neighbor of BRCA1 gene 1) is a protein that is ubiquitously expressed and highly conserved in eukaryotes. This protein is associated with cellular signaling pathways. NBR1 is a binding partner of autophagy-related protein 8 (ATG8) family proteins, including LC3.


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The ATG8 functions in the formation of autophagosome, similar to yeast ATG8. NBR1 functions as a cargo adaptor for autophagic degradation of ubiquitinated substrates in a similar way as does p62. Recent studies indicated that NBR1 is located in Lewy bodies and glial cytoplasmic inclusions in multiple system atrophy, suggesting that it has a binding preference for α-synucleinopathy-related molecules (Odagiri et al., 2012). Relatively recently it was clarified that there are two types of autophagy, starvationinduced autophagy and selective autophagy, each with a different role, although both types use the same autophagy core machinery. Guillebaud and Germain (chapter in Autophagy, Volume 8) have compared selective autophagy with starvation-induced autophagy and reported that these two types are partially distinct from each other; the former degrades large intracellular aggregates and dysfunctional organelles to lessen the occurrence of neurodegenerative diseases, while the latter promotes nutrient recycling and survival. It is suggested that the starvation-induced autophagy may promote survival of cancer cells, while the selective autophagy plays a survival role in neurons by preventing the accumulation of potentially toxic damaged cellular components. Sixteen types of selective autophagies are discussed below.

Allophagy In sexual reproduction gamete fusion leads to the combination of two nuclear genomes, but the fate of paternal mitochondrial DNA requires explanation. Cumulative evidence indicates that in most animals, including humans, paternal mitochondria usually are eliminated during embryogenesis, a process termed allophagy, which is accomplished through autophagy. A number of mechanisms have been proposed to explain allophagy. Some years ago Gyllenstein et al. (1991) hypothesized that according to the “simple dilution model,” the paternal mitochondrial DNA (present at a much lower copy number) is simply diluted away by the excess of oocyte mitochondrial DNA, and consequently the former is hardly detectable in the offspring. On the other hand, according to the “active degradative process,” the paternal mitochondrial DNA or mitochondria themselves are selectively eliminated (either before or after fertilization) by autophagy, preventing their transmission to the next generation (Al Rawi et al., 2012). As indicated earlier, uniparental inheritance of mitochondrial DNA is observed in many sexually reproducing species and may be accomplished by different strategies in different species. Sato and Sato (2013) have proposed the following strategies. 1. Diminished content of mitochondrial DNA during spermatogenesis. 2. Elimination of mitochondrial DNA from mature sperms. 3. Prevention of sperm mitochondria from entering the oocyte. 4. Active degradation of the paternal mitochondrial DNA in the zygote. 5. Selective degradation of the whole paternal mitochondria (mitophagy) in the zygote. The most feasible mechanism to accomplish this goal in mammals is as follows. Spermderived mitochondria and their DNA enter the oocyte cytoplasm during fertilization and temporarily coexist in the zygote alongside maternal mitochondria. However, very shortly after fertilization, paternal mitochondria are eliminated from the embryo. Thus,


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mitochondrial DNA is inherited solely from the oocyte from which mammals develop. This also means that some human mitochondrial diseases are caused by maternal mitochondrial DNA mutations. The embryo of C. elegans nematode has been extensively used as an experimental model for exploring the role of autophagy in the degradation of paternal organelles (Al Rawi et al., 2012). They have shown that paternal mitochondrial degradation depends on the formation of autophagosomes a few minutes after fertilization. This macroautophagic process is preceded by an active ubiquitination of some spermatozoon-inherited organelles, including mitochondria. The signal for such degradation is polyubiquitination of paternal mitochondria. Sato and Sato (2012) have also reported the selective allophagy in such embryos. It should be noted that the elimination of paternal mitochondrial DNA is not universal. Paternal inheritance of mitochondrial DNA, for example, has been reported in sheep and lower primates (Zhao et al., 2004; St. John and Schatten, 2004). A recent study using mice carrying human mitochondrial DNA indicated that this DNA was transmitted by males to the progeny in four successive generations, confirming the paternal transmission of mitochondrial DNA (Kidgotko et al., 2013). Apparently, human mitochondrial DNA safely passed via male reproductive tract of several mice in several generations. This and a few other studies invoke a question regarding the existence of a specific mechanism responsible for paternal mitochondrial DNA transmission. Another pertinent, more important unanswered question is: why paternal mitochondria and/or their DNA are eliminated from embryos? One hypothesis is that paternal mitochondria are heavily damaged by ROS prior to fertilization and need to be removed to prevent potentially deleterious effect in the next generation (Sato and Sato, 2012).

Axonophagy (Neuronal Autophagy) Selective degradation of axons under pathological conditions is termed axonophagy, which is directly linked to CNS and spinal cord neurodegenerative disorders, including PD, AD, HD, and amyotrophic lateral sclerosis. They exhibit axonal degeneration early in the disease course; examples are degeneration of nigrostriatal projection tracts in PD and corticospinal tracts in amyotrophic lateral sclerosis. Neurons have developed specific mechanisms for regulating autophagy. However, neuronal autophagic activities can be altered by pathological conditions including neurodegenerative diseases as shown by the accumulation of autophagosomes (Rubinszstein et al., 2005). Large numbers of autophagosomes are frequently found in axonal dystrophic terminals of degenerating neurons (Yue, 2007). Autophagy is more pronounced in axons than in the cell body and dendrites under excitotoxic insult. It has been proposed that p62/SQSTM1 (a putative autophagic substrate) can serve as a marker for evaluating the impairment of autophagic degradation (Yue, 2007). Autophagosomes formed in the distal ends of axons may undergo retrograde axonal transport back to the cell body where lysosomes are usually located for completion of degradation. Sequential features of axonal degeneration are elaborated below. The distal part of the lesioned axon undergoes initial axonal stability followed by rapid degeneration and blebbing of the remaining axons, microtubule disassembly, and phagocytic clearance of the lesion site (Knöferle et al., 2010). In contrast to this mechanism, axon degeneration occurs


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within the first minutes after lesion in the case of acute axonal degeneration in the spinal cord. One of the putative initiating steps in axonal degeneration is the influx of extracellular calcium, which destabilizes the axon and transmits apoptotic signals to the neuronal soma (Ziv and Spira, 1995). Role of calcium and autophagosomes in axonophagy is discussed below. Autophagosomes play a critical role in the axonophagy process, and calcium plays a crucial role in their formation. This process has been investigated in the axonal degeneration in the optic nerve in vivo (Knöferle et al., 2010). It was shown that mechanical injury to the optic nerve induced extracellular calcium entry to the axolemma via calcium channels, which resulted in rapid increase of Ca2+. This results in secondary generation of autophagosomes and axonal degradation.

Chromatophagy It is known that autophagy is the principal catabolic prosurvival pathway during nutritional starvation. However, excess autophagy can be cytotoxic, resulting in cell death. The leakage of DNA, histones, and other chromatin-associated proteins are captured by autophagosomes, and this process is referred to as chromatin autophagy or chromatophagy. Chromatophagy creates an environment within the cell, and as a result, organelles cannot function correctly, resulting in the activation of autophagy. It is known that autophagy via lysosomes degrades dysfunctional organelles. In the absence of functional organelles, cell, of course, will die. It is also known that starvation activates autophagy. For example, when cell is deprived of amino acid arginine (using arginine deiminase), mitochondria become dysfunctional and produce large amounts of oxidation compounds, which damage the chromatin (proteins and DNA), activating autophagy (Changou et al., 2014). Arginine starvation specifically kills tumor cells by a novel mechanism involving mitochondria dysfunction, generation of ROS, DNA leakage, and chromatin autophagy (chromatophagy). A huge level of giant autophagosomes and autolysosomes encapsulating the leaked DNA is found in the arginine-deprived dying cells (Changou et al., 2014). The specificity mentioned earlier is expected because tumor cells and normal cells differ in their metabolic requirements. The most prominent examples are addiction of tumor cells to glucose (the Warburg effect) and to glutamine (Vander Heiden et al., 2009; Dang, 2010). Starvation of cells from amino acids, especially from arginine and glutamine, results in the death of cells, preferentially tumor cells. Argininosuccinate synthetase 1 (ASS1), a rate limiting enzyme for intracellular arginine synthesis, shows reduced expression in many cancer types such as bladder cancer (Allen et al., 2014). Another example is treatment of prostate cancer cells with ADI-PEG20, which causes DNA leakage, and this DNA together with histones and other chromatin-associated proteins are captured by LC3-containing autophagosomes. Pegylated arginine deiminase (a recombinant mycoplasma protein) converts arginine to citrulline and removes extracellular arginine. This approach has been approved by the FDA for phase III clinical trials in hepatocellular carcinoma (You et al., 2013). Thus, amino acid starvation therapies against tumors have been developed and have reached to clinical trials (Cheng et al., 2007). The starvation therapies have the advantage over radiation and chemotherapy because the former shows lower toxicity.


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Cell death caused by chromatophagy differs from that by apoptosis. Piecemeal microautophagy of the nucleus (PMN) also differs from chromatophagy because PMN occurs in lower eukaryotic cells, and degradation of nuclear cargo is through nuclear-vacuole junctions and does not involve the formation of an autotphagosome (Kung et al., 2015). In contrast, chromatophagy cell death is induced by a combination of excessive autophagy and ROS. Chromatophagy is accomplished via a double-membraned structure, derived from fusion between an autophagosome membrane and the nuclear membrane. As mentioned earlier, chromatin is leaked from the nucleus because of elevated level of ROS. The concept of the involvement of ROS is strengthened by the evidence that N-acetylcysteine (ROS scavenger) reduces chromatophagy phenotype (Kung et al., 2015). Excessive ROS damages nuclear DNA and membrane and induces autophagy, which is observed in chromatophagy. However, it needs to be noted that ROS modulates autophagy and vice versa. Some information regarding the role of mitochondria in chromatophagy is available. Prolonged arginine depletion impairs mitochondrial oxidative phosphorylation function and depolarizes mitochondrial membrane potential. Thus, ROS production increases significantly in both cytosolic and mitochondrial fractions, leading to the accumulation of DNA damage (Changou et al., 2014). This evidence suggests that mitochondrial damage is central to linking arginine starvation and chromatophagy. This suggestion is supported by knowing that the additions of ROS scavenger N-acetyl cysteine or knockdown of Atg5 or Beclin 1 reduces chromatophagy. Arginine starvation has emerged as a potential therapy for cancers as they show selective deficiency of the arginine metabolism. Thus, arginine depletion by the enzyme arginine deiminase induces a cytotoxic autophagy in cancer cells. A novel phenotype with giant autophagosomes, nuclear membrane rupture, and histone-associated DNA leakage encaptured by autophagosomes is found in arginine-deprived dying cells (Changou et al., 2014). In conclusion, based on the above and other information, mitochondrial ROS regulates chromatophagy (Changou et al., 2014). Chromatophagy has been observed in prostate cancer, pancreatic cancer, and urinary bladder cancer cell lines (Kung et al., 2015). Clinical use of chromatophagy in the future to overcome the resistance of cancer to standard therapies is projected. However, additional information is needed to recommend the ADI-induced chromatophagy for treating malignant diseases. The questions needed to be answered are: how widespread is the phenotype in arginine-depended cancers? Is it restricted to arginine alone, and how can this process be measured in vivo (Changou et al., 2014)? For additional related information, see “Nucleophagy” section in this chapter.

Ciliophagy Cilia are microtubule-based structures located at the surface of many cell types. An interplay between cilia and autophagy has been reported. Signaling from the cilia recruits the autophagic machinery to trigger autophagosome formation (Orhon et al., 2015). On the other hand, autophagy regulates ciliogenesis by controlling the levels of ciliary proteins. Sequestration of cilia proteins by autophagy in response to cigarette smoking is termed ciliophagy. COPD involves aberrant airway inflammatory response to cigarette smoke, which is associated with respiratory epithelial cell cilia shortening and impaired


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mucociliary clearance (Cloonan et al., 2014). Impaired airway clearance prevents the elimination of dust particles, pathogens, etc., trapped in mucus from the airways. Increased autophagy in the lungs of COPD has been reported (Cloonan et al., 2014). Cilia components function as autophagic substrates during cigarette smoking. Cilia proteins are sequestered within autophagosomes in response to exposure to cigarette smoke. Cilia shortening occurs through an autophagy-dependent mechanism mediated by the HDAC6, the inhibition of which by tubastatin A, protects mice from cigarette smoking-associated mucociliary dysfunction. Indeed, autophagy-dependent pathway regulates cilia length during cigarette smoking, and may disrupt airway epithelial cell function. This disruption reduces epithelial cell cilia length and death of these cells.

Crinophagy Disposal of excess secretory granules containing insulin by fusion of these granules with lysosomes is termed crinophagy. The β cells in the pancreatic islets are involved in the storage of insulin secretory granules and instant secretion of insulin. These cells must maintain an optimal insulin concentration, which is maintained by insulin biosynthesis and its intracellular degradation. Such degradation is carried out via crinophagy, i.e., β-cell lysosomes are subjected to glucose-dependent alterations. At low or physiological glucose concentration, secretory granules containing insulin are common in β-cell lysosomes. As mentioned earlier, crinophagy in these cells is glucose-dependent, and variations in glucose concentration affect the balance between insulin biosynthesis and secretion, which is under direct molecular control. It has been demonstrated that intracellular degradation of insulin and crinophagy are regulated by COX-2 activity that is maintained by endogeneous nitric oxide (NO) (Sandberg and Borg, 2006). It has also been demonstrated that incubation of isolated pancreatic islets with interleukin 1β (IL-1β) enhances the intracellular degradation of insulin (Sandberg and Borg, 2006). It is known that IL-1β causes expression of inducible NOs in pancreatic islets. It is concluded that considerable amounts of insulin are degraded within the pancreatic β cells at low or physiological glucose concentrations, whereas there is virtually no degradation at a high glucose concentration (Halban and Wollheim, 1980). This mechanism seems to control the intracellular degradation of insulin and crinophagy in pancreatic β cells.

Exophagy Exophagy is defined as the process by which proteins are secreted into the extracellular space by using an unconventional secretion method. The conventional route of passage of proteins is from ribosomes to the ER, Golgi complex, and extracellular space. Signal peptides are involved in this passage. An estimated 30% of human genes encode proteins carrying an N-terminal amino acid sequence that targets most of them to the ER for transportation to the Golgi and then finally to the extracellular space by conventional mode of protein secretion. Some proteins lack an N-terminal signal sequence and do not follow the conventional secretory pathway, and this process is called unconventional protein secretion. Such proteins include insulin-degrading enzymes, angiogenic fibroblast growth factor 1 (FGF1), and


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interleukin-1X. Several mechanisms have been suggested for the secretion of such proteins (Nickel and Rabouille, 2009), some of which are summarized here. Acyl coenzyme A (CoA)–binding protein AcbA is one of such proteins, the secretion of which is dependent on Golgi reassembly and stacking protein (GRASP) (Manjithaya et al., 2010). The secretion, processing, and function of an AcbA-derived peptide (SDF-2) are conserved in yeasts Pichia pastoris and S. cerevisiae. It has been shown that in yeast the secretion of SDF-2-like activity is GRASP-dependent, triggered by nitrogen starvation, and requires autophagy proteins and medium-chain fatty acyl CoA generated by peroxisomes (Manjithaya et al., 2010). Duran et al. (2010) suggest that autophagosomes containing the cargo for unconventional secretion evade fusion with the yeast vacuole, preventing its degradation. These autophagosome intermediates fuse with recycling endosomes and form multivesicular bodies, which then fuse with the plasma membrane to release already selected cargo. The conserved role of Golgi-associated protein GRASP in starvation-induced unconventional secretion in Dictyostelium discoideum has also been reported (Duran et al., 2010). This study indicates the involvement of autophagy genes and the plasma membrane SNARE. Another mechanism explaining the export of such proteins is based on the Cu2+-dependent formation of multiprotein complexes containing the S100A13 protein. Prudovsky et al. (2003) suggest that this protein complex is translocated across the plasma membrane as a “molten globule.” This protein is involved in pathological processes. Also, it has been suggested that acyl-CoA-binding protein is sequestered into autophagic vesicles that subsequently are rerouted to the plasma membrane where their content is released into the extracellular space (Abrahamsen and Stenmark, 2010). Several questions arise. How does the AcbA-containing secretory autophagic vesicle reach to the plasma membrane instead of the yeast vacuole? Second question is what is the difference between AcbA vesicles and degenerative autophagic vesicles? Another question is how the cargo is sorted for packaging into autophagosomes for extracellular release rather than degradation in lysosomes/vacuoles. It seems that several transport mechanisms are involved in the nonconventional secretion of proteins. Future studies will be required to explicitly clarify the role of autophagosomes/autophagy in the transport of proteins selected for unconventional secretion into the extracellular space. Another protein, α-synuclein, involved in unconventional secretion in neurodegenerative diseases is discussed here. It is known that PD is characterized by the progressive loss of dopaminergic neurons in the substantia nigra, although other neural populations of the central nervous system also play a role in this disorder. The progression of PD is a slow process accompanied by the involvement of an increasingly larger volume of the nervous system. It is thought that progression of this disease correlates with a spreading pattern of α-synuclein inclusion body disease throughout the nervous system (Braak et al., 2003). Alpha-synuclein protein is abundant in the human brain, and smaller amounts are also found in the heart, muscles, and other tissues. This protein aggregates to form insoluble fibrils in pathological conditions characterized by Lewy bodies as in PD. Alpha-synuclein is the primary structural component of Lewy body fibrils. It has been demonstrated that neurons are capable of secreting and internalizing α-synuclein (Desplats et al., 2009). Aggregated or modified forms of α-synuclein are degraded by proteasome, macroautophagy (autophagy), and CMA (Vogiatzi et al., 2008). The role of autophagy in the clearance of α-synuclein was recently further studied. Ejlerskov et al. (2013) have demonstrated that de novo expressed p25α


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colocalizes with α-synuclein and causes its aggregation and distribution into autophagosomes in PC12 catecholaminergic nerve cells. Aggregation of α-synuclein can be promoted by tubulin polymerization-promoting protein, p25α. However, p25α also lowers the mobility of autophagosomes and hinders the final maturation of autophagosomes by preventing their fusion with lysosomes for the final degradation of this protein (Ejlerskov et al., 2013). The secretion of α-synuclein is strictly dependent on autophagy and could be upregulated (trehalose, Rab1A) or downregulated (3-methyladenine, ATG5 shRNA) by enhancers or inhibitors of autophagy, respectively. Both secretion of α-synuclein and lysosomal fusion block can be replicated by knockdown of the p25α target, HDAC6 (the predominant cytosolic deacetylase in neurons). In conclusion, unconventional secretion of α-synuclein can be mediated through exophagy. Increased extracellular secretion of α-synuclein is based on the exocytosis of autophagosomes and amphisomes containing α-synuclein.

Glycophagy The delivery of glycogen to lysosomes for degradation is termed glycophagy. Three types of enzymes convert glucose into uridin diphosphoglucose, the primary intermediate in glycogen synthesis. The glucose residue of the intermediate molecule is transferred by glycogen to the free hydroxyl group on carbon 4 of a glucose residue at the end of a growing glycogen chain. Glycogen functions as a reserve for glucose and provides intracellular energy reserve in many types of cells. Glycogen is especially abundant in liver and muscle cells. As much as 10% by weight of the liver can be glycogen. The presence of glycogen particles in the vicinity of the smooth endoplasmic reticulum (SER) membranes in the liver as well as in the sarcoplasmic reticulum membranes in the muscle is commonly seen using electron microscopy (M.A. Hayat). Glycogen is also present in lysosomes of mammalian cells where it is directly hydrolyzed by lysosomal acid alpha-glucosidase (acid maltase). Deficient glucosidase causes severe glycogen storage diseases (Pomp disease, cardiopathologies). Normally, synthesis and degradation of glycogen are highly regulated according to need. Accumulation of glycogen tends to cause a severe glycogen storage disease, Pomp disease, in multiple tissue types, especially in skeletal and cardiac muscles. The buildup of glycogen forms a large mass that interrupts the contractile proteins of the skeletal muscle fibers, affecting muscle contraction (Fukuda et al., 2006), muscular weakness, and eventual tissue destruction. Other glycogen diseases include Anderson disease (Chen and Burchell, 1995), Tarui disease (Nakajima et al., 1995), and Lafora disease (Andrade et al., 2007). Some information is available explaining the glycogen trafficking to the lysosomes and its degradation. Autophagy seems to be involved in this process. The starch-binding domain-containing protein 1 (Stbd 1) (genethonin 1) participates in this mechanism by anchoring glycogen to intracellular membranes via its N-terminus (Janecek, 2002; Jiang et al., 2011). Degradation of glycogen occurs by removing glucose residues catalyzed by glycogen phosphorylase. Stbd 1 targets two autophagy-related proteins, GABARAP and GABARAPL 1. Stbd 1 acts as a cargo receptor for glycogen. The Atg8 family interacting motif (AIM) in Stbd 1 is responsible for its interaction with GABARAPL 1(Jiang et al., 2011). Stbd 1 is thought to function as a cargo-binding protein that delivers glycogen to lysosomes in an autophagic pathway (glycophagy). In fact, Stbd 1 is considered to be a glycophagy marker.


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Lipophagy A vast majority of studies of autophagy in the past rightfully have emphasized its role in cellular energy balance, cellular nutritional status, cellular quality control, remodeling, and cell defense. In most of these studies emphasis was placed on the role of autophagy in supplying energy through degradation of proteins to obtain amino acids required to maintain protein synthesis under the extreme nutritional conditions. However the contribution of autophagy to maintain the cellular energetic balance is not solely dependent on its capacity to provide free amino acids (Singh and Cuervo, 2012). Free amino acids are relatively inefficient source of energy when oxidized to urea and carbon dioxide. In contrast, free fatty acids and sugars are more efficient in supplying energy, especially the former through lipophagy. Lipophagy is a selective form of autophagy and refers to the degradation of lipid droplets by stimulating autophagy. Lipid droplets are intracellular storage deposits for neutral lipids that are widely present in cells ranging from bacteria to humans. These droplets are considered to be an organelle enclosed by a polar lipid monolayer membrane. They contain the hydrophobic core of triglycerides, diacyglycerol, cholesterol ester, and other esters. Mobilization of lipids inside the lipid droplets occurs through lipolysis. Cells activate lipolysis when they need energy and also when lipid storage becomes too large. The synthesis of fatty acids and phospholipids occurs in the smooth endoplasmic reticulum (SER). Autophagy has been implicated in the degradation of several types of intracellular components, but only relatively recently have cytoplasmic lipid droplets been added to the list. This process of lipophagy has raised the likelihood that autophagy is involved in the regulation of lipoprotein assembly and contributes to both intracellular and whole-body lipid homeostasis (Christian et al., 2013). Thus, autophagy is thought to be partially responsible for the upregulation or downregulation of very low–density lipoprotein assembly. It means that autophagy is involved in the regulation of lipid accumulation during adipocyte differentiation. Lipophagy breakdowns triglycerides and cholesterol stored in lipid droplets, regulating intracellular lipid content. This degradation supplies free fatty acids required to sustain cellular rates of mitochondrial levels of ATP. In other words, lipophagy maintains cellular energy homeostasis. Intracellular lipids, in addition, function as structural components of membranes building blocks for hormones and mediators of cell signaling. The amount of lipid targeted for autophagic degradation depends on the nutritional status. Another important function of autophagy is in liver diseases, which are characterized by the accumulation of triglycerides and irregular lipid metabolism within the liver. It has been reported that suppression of autophagy pathway leads to the accumulation of lipid droplets in hepatocytes and other cell types (Singh et al., 2009). Aberrant autophagy is also involved in conditions of deregulated lipid homeostasis in metabolic disorders such as metabolic syndrome of aging (Christian et al., 2013). Lipophagy is also functionally involved in hypothalamic neurons and macrophage foam cells (Kaushik et al., 2011; Ouimet et al., 2011). A variety of proteins (Rab and PAT) are also associated with the lipid droplet membrane. PAT proteins regulate cytosolic lipase–mediated lipolysis, a major pathway for regulating lipid homeostasis (Fujimoto et al., 2008). Impaired lipophagy, indeed, is a fundamental mechanism of disorders of lipid metabolism such as obesity,


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diabetes, and atherosclerosis. The initial accumulation of excess lipid is referred to as steatosis (Czaja, 2010). Role of lipophagy in the alcohol-induced liver is discussed later. In addition to the role played by lipophagy in the already mentioned diseases, the role of lipid accumulation in the cardiovascular diseases was recently studied by Kim et al. (2013). Epigallocatechin gallate (EGCG) is a major polyphenol in green tea, which has beneficial health effects in the prevention of cardiovascular disease. These authors suggest that EGCG regulates ectopic lipid accumulation through a facilitated lipophagy flux. Treatment with EGCG increases the formation of LC3-II and autophagosomes in bovine aortic endothelial cells. Activation of CaMKKβ is required for EGCG-induced LC3-II formation. This effect is due to cytosolic Ca2+ load. It is concluded that EGCG induces lipophagy through a reduction in the accumulation of lipid droplets in endothelial cells. It is known that impairment of lysosomal degradation process reduces autophagic flux leading to serious disorders in cardiovascular and metabolic tissues (Singh and Cuervo, 2011). The following questions still remain to be answered and open for future studies (Singh and Cuervo, 2012): 1. Is there any similarity between the signaling pathways that regulate lipophagy and those for other types of autophagy? 2. What is the molecular mechanism underlying the selective targeting the lipid droplets by lipophagy? 3. Is there a subset of lipid droplets that is targeted by lipophagy? 4. Is there a difference between the lipid products produced by lipophagy and those arising from lipolysis? 5. How does the switch take place from a stimulatory to an inhibitory effect of free fatty acids on lipophagy? 6. Does upregulation of lipophagy protect cells from lipotoxicity? 7. Does defective hypothalamic lipophagy contribute to the reduced food intake at an advanced age? 8. What is the potential of developing a therapeutic intervention against metabolic disorders by organ-specific targeting of this process? An interesting role of lipophagy and mitophagy in chronic ethanol-induced hepatic steatosis, has been reported by Eid et al., (2013). It is known that chronic alcohol intake may induce alcoholic disease, ranging from early-stage steatosis (fatty liver) to steatohepatitis, fibrosis, cirrhosis, and finally hepatic cancer (Yan et al., 2007). Rats fed with 5% ethanol in liquid diet for 10 weeks showed large lipid droplets and damaged mitochondria in steatolic hepatocytes (Eid et al., 2013). Moreover, hepatocyte steatosis was associated with enhanced autophagic vacuole formation compared to control hepatocytes. In addition, LC3 (a marker for autophagosomes) demonstrated an extensive punctate pattern in hepatocytes of these experimental rats. Furthermore, PINK1 (a sensor damaged mitochondria, mitophagy) as well as LAMP-2 (a marker of autolysosomes) were expressed in these rats. This information is a clear evidence of ethanol toxicity because of the accumulation of lipid droplets in the cytoplasm of hepatocytes involving lipogenesis and lipolysis. Elevated levels of lipophagy and mitophagy reduce hepatocyte cell death under acute ethanol toxicity (Ding et al., 2011b).


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In conclusion, the enhanced autophagic sequestration of accumulated lipid droplets and damaged mitochondria may occur in the presence of endogenous LC3-II, LAMP-2, PINK 1, pan cathepsin, and cytochrome c under chronic ethanol toxicity. Nevertheless, the available information is insufficient to explain the relationship between lipophagy and canonical autophagy as well as between lipophagy and cytosolic lipolysis. The deciphering of the molecular mechanism underlying such differences may provide new therapeutic tools.

Lysophagy It is known that lysosomes contain acidic hydrolases that degrade cell macromolecules delivered to them via autophagic and endocytic pathways. However, lysosomes can also be ruptured under certain conditions (e.g., pathogenic invasion, bacterial and viral toxins, uptake of minerals), releasing digestive enzymes in the cytosol, which results in the destruction of normal intracellular structures and their functions (Boya and Kroemer, 2008). Lysosomal rupture can also lead to oxidative stress, inflammation, apoptosis, and necrosis. Recently, it was reported that intracellular irritative particles such as human islet amyloid polypeptide, cholesterol crystals, and monosodium urate lead to lysosomal damage (Maejima et al., 2013). As a result, autophagic machinery is recruited only for damaged lysosomes that are engulfed by autophagosomes in mammalian cells (Hung et al., 2013). Such autophagy is indispensable for cellular homeostasis. Lysophagy is thought to be an ubiquitin-mediated process involving LC3 and p62, which contributes to the recovery of lysosomal activities (Maejima et al., 2013). Further information is awaited to explain how ubiquitin and core Atg proteins selectively target damaged lysosomes.

Mitophagy It is thought that after its endosymbiosis from α-proteobacterial ancestor, mitochondrial genome was streamlined into a small, bioenergetically specialized genetic system, allowing individual mitochondrion to respond through gene expression to alterations in membrane potential and maintain oxidative phosphorylation. Replication and transcription of mitochondrial DNA is initiated from a small noncoding region and is regulated by nuclearencoded proteins that are posttranslationally imported into mitochondria. Mitochondria possess a unique genetic system that is able to translate the mitochondria-encoded genes into 13 protein subunits of the electron chain. Mercer et al. (2011) have presented analysis of the mitochondrial transcription across multiple cell lines and tissues, revealing the regulation, expression, and processing of mitochondrial RNA. This information should help in the understanding of exceedingly complex function of mitochondria. The major functions of mitochondria are summarized below. Mitochondria fulfill central roles in oxidative phosphorylation, in energy metabolism, in the synthesis of amino acids, lipids, heme, and iron sulfur clusters, in ion homeostasis and in thermogenesis. The most important role of mitochondria is to provide energy to aerobic eukaryotic cells by oxidative phosphorylation. Thus, these organelles are essential for growth, division, and energy metabolism in these cells. Each cell usually contains hundreds of mitochondria, and without these organelles even cancer cells are unable to grow, multiply, and survive in vivo. Mitochondrial dysfunction is strongly linked to numerous


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neurodegenerative and muscular disorders, myopathies, obesity, diabetes, cancer, and aging (Detmer and Chan, 2007). Minimizing mitochondrial dysfunction is thus of major importance for counteracting the development of numerous human disorders and the aging process. Mitochondria also play a crucial role in apoptosis and autophagy. It is apparent that mitochondria are central to the two fundamental processes of cell survival and cell death. Mitophagy plays a major role in the specific recognition and removal of damaged mitochondria, and thus in mitochondrial quality control. The quality control of mitochondria does occur naturally at different levels. On the molecular level, dysfunctional mitochondria are recognized and degraded within cells by autophagy. Mitochondria can be degraded both by nonselective autophagy and by mitophagy. Engulfment of mitochondria by autophagosomes is observed under starvation conditions as well as when mitochondrial function is impaired. Mitochondrial turnover is necessary for cellular homeostasis and differentiation. Mitochondria are replaced every 2–4 weeks in rat brain, heart, liver, and kidney. The removal of dysfunctional mitochondria is achieved through mitophagy. Mitophagy is responsible for the removal of mitochondria during terminal differentiation of red blood cells and T cells. Mitochondria are recognized for selective mitophagy either by PINK1 and Parkin or by mitophagic receptors Nix and Bnip3 and their accompanying modulators (Novak, 2012). The former mitophagy recognizes mitochondrial cargo through polyubiquitination of mitochondrial proteins. Nix functions as a regulated mitophagy receptor. These two modes of capturing mitochondria function at different efficiencies, from partial to complete elimination of mitochondria. In addition to autophagy machinery, proteins associated with mitochondrial fusion and fission regulate mitochondrial morphology, which is discussed elsewhere in this chapter. A number of factors required for mitophagy have been identified and their role in this process has been analyzed. NIX (aBH3 domain-containing protein) acts as a mitochondrial receptor required for mitochondrial clearance in some types of cells (e.g., reticulocytes). Many studies have shown that PINK1 and Parkin are involved in mitophagy. Mitochondrial depolarization induced by protonophore CCCP, downregulation of PINK1, and ROS induce mitophagy as well as nonselective autophagy. More importantly, mitochondrial fission is necessary for the induction of mitophagy.

Nucleophagy Cell nucleus is an organelle bounded by a double membrane, which undergoes drastic reorganization during major cellular events such as cell division and apoptosis. Nucleophagy (macroautophagy) is involved in the elimination of whole nuclei, micronuclei, or chromatin; for additional information related to chromatin elimination, see “Chromatophagy” section in this chapter. Alternatively, only parts of the cell nucleus can be selectively degraded without killing the cell. It is known that nucleophagy plays a part in the maintenance of genome stability. Nucleophagy is evoked after genotoxic stress in the context of various biological processes, including endopolyploidy. Failure of DNA repair serves as a signal for the chromatin autophagy of micronuclei. Recently the elimination of micronuclei from osteosarcoma cells was reported by Rello-Varona et al. (2012).


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Nucleophagy in multinucleated cells favors depolyploidization. This process mitigates aneuploidy with its adverse effects, promoting the survival fitness of descendents and treatment resistance (Erenpreisa et al., 2012). The process of nucleophagy is best described in the budding yeast, S. cerevisiae. Under certain conditions, the removal of damaged or nonessential parts of the nucleus or even an entire nucleus (differentiation or maturation of certain cells) is necessary to promote cell longevity and normal function; such degradation and recycling are accomplished via nucleophagy (Mijaljica and Devenish, 2013). Autophagic degradation of the nucleus in mammalian cells as a “housecleaning” under normal and disease conditions has been studied (Mijaljica et al., 2010). Molecular mechanisms underlying the formation of nucleus–vacuole junctions that mediate nucleophagy in the yeast have been deciphered (Roberts et al., 2003). This mediation is accomplished through specific interactions between Vac8p on the vacuole membrane and Nvj1p in the nuclear envelope. Electron microscopy has shown that portions of the nucleolus are sequestered during nucleophagy (Mijaljica et al., 2012). Morphologically, during nucleophagy a nuclear bleb containing the nuclear cargo is pinched off from the nucleus and directly engulfed and sequestered into an invagination of the vacuolar membrane rather than packaged into autophagosome-like vesicles. It has been shown that upon nitrogen starvation the initiation of piece meal micronucleophagy of the nucleus (PMN) occurs, as stated above, at nucleus–vacuole junction between the outer nuclear membrane protein, Nvj1p, and the vacuolar membrane protein, Vac8p (Krick et al., 2008). Recently, it was demonstrated that induction of PMN can be detected as early as after 3 h of nitrogen starvation (Mijaljica et al., 2012). These authors employed genetically encoded nuclear fluorescent reporters (n-Rosella). The PMN occurs through a series of morphologically distinct steps: (1) a nucleus–vacuole junction is formed at the nuclear envelope (both inner and outer membranes are involved); (2) simultaneous invagination of the vacuolar lumen; and (3) the nuclear derived double membranous structure containing nuclear material undergoes fission and is degraded by vacuolar hydrolases. This efficient process requires core ATG genes (Krick et al., 2008). All four components of the Atg8p-PE conjugation system (ATG3, ATG4, Atg7, and ATG8) have been reported to be essential for efficient late nucleophagy. The role of lipid trafficking membrane proteins in the mechanism of late nucleophagy is important. Kvam and Goldfarb (2004) have proposed that yeast Osh proteins play a general role in lipid trafficking at membrane contact sites between different organelles including the nucleus and vacuole. Roberts et al. (2003) have shown that upon nitrogen starvation and concomitant increased expression of Nvj1p, two proteins Osh1 and Tsc13p were required for PMN. In spite of the known molecular mechanisms discussed above, the specific conditions under which various cell nucleus components, such as nucleoli, chromosomes, chromatin, histones, nuclear pore complexes, and nucleoplasm, are degraded are not known. For additional related information, see “Chromatophagy” section in this chapter.

Pexophagy The peroxisome organelle is found in humans (especially in liver and kidney), fungi, protozoa, algae, and plants. It is surrounded by a single membrane. Peroxisome numbers are


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highly regulated in a cell in response to changes in the metabolic status, depending on the cellular needs. They are also required for the synthesis of essential cellular components such as plasmogens, isoprenoids, and lysine (Farré et al., 2013). Peroxisomes are dynamic metabolic organelles that are required for oxidation of fatty acids and reduction of hydrogen peroxide produced during lipid oxidation (Deosaran et al., 2013). Peroxisomes also break down methanol, ethanol, formaldehyde, and some types of amino acids. Peroxisomes are also involved in antiviral innate immunity and antiviral signaling (Dixit et al., 2010). The inability to maintain adequate number of peroxisomes is linked to various neurodegenerative diseases. The selective degradation of dysfunctional peroxisomes by autophagy is referred to as pexophagy. Pexophagy is increased or decreased in response to changes in the metabolic state of the cell or the tissue. The substrate selection is mediated by ubiquitylation recruitment of ubiquitin-binding autophagic receptors, including NBR1, p62, NDP52, and Optineurin. Mutagenesis studies of the NBR1 receptor indicate that the amphipathic α-helical domain, the ubiquitin-associated (UBA) domain, the LC3-interacting region, and coiled-coil domain are necessary to mediate mammalian pexophagy (Deosaran et al., 2013). These authors indicate that although p62 is not essential in the presence of sufficient NBR1, the binding of the former to the latter increases the efficiency of the NBR1-mediated pexophagy. Thus, NBR1 is the specific autophagic receptor for pexophagy in mammalian cells as NBR1 can promote pexophagy in the absence of p62. Role of Pexophagy in Yeast The role of pexophagy in the lives of at least three types of yeasts (P. pastoris, S. cerevisiae, and Hansenula polymorpha) has been extensively studied. Autophagy in these organisms is mainly a survival response to nutrient starvation. Two receptors have been described in S. cerevisiae: Atg19 (cytoplasmic-to-vacuole targeting, Cvt) pathway and Atg36; one receptor in P. pastoris: Atg30, and two receptors, Pex5p and Pex20p, in H. polymorpha. Atg19 interacts directly with the cargo (aminopeptidase 1, Apel 1) to form the Cvt complex, and subsequently with two autophagy proteins, Atg11 and Atg8 (Shintani et al., 2002). Atg11 is a required protein for most selective autophagy pathways in yeast and functions as a basic scaffold in assembling the specific phagophore assembly site (PAS) by interacting directly with the receptor, with itself, and several other proteins such as Atg1, Atg9, and Atg17 to form the PAS (Yorimitsu and Klionsky, 2005). Some information is available on how the above-mentioned and other receptors interact with their partners. Farré et al. (2013) report the presence of a phosphoregulatable AIM) on Atg30, Atg32, and Atg36; this motif is required for their interactions with Atg8. Mutations of these consensus motifs explain the mechanism of interactions between the receptors and the autophagy proteins. Atg30 protein is located on the peroxisomal membrane via its interaction with two peroxisomal proteins, Rex14p and Pex3p (Farré et al., 2008). In contrast to mammalian pexophagy receptors, Atg30 does not directly interact with Atg8 but interacts with Atg11 and Atg17 in order to target peroxisomes to autophagosomes. This interaction requires phosphorylation of Atg30. Atg30 receptor, in addition, does not have an ubiquitin-binding domain, indicating that its targeting is not ubiquitin dependent. However, in S. cerevisiae, another receptor, Atg36, binds to Pex3p on peroxisomes and to Atg8 and the adaptor Atg11 (Motley et al., 2012). The role of the specific protein, PpAtg30, in mediating peroxisome selection during pexophagy of P. pastoris has been explained (Farré et al., 2008). Although this protein is required


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for pexophagy, it is not necessary for other selective or nonselective autophagy-related processes. During pexophagy, this protein is subjected to multiple phosphorylations, at least one of which is required for pexophagy. PpAtg30 is considered to be an important player in selecting peroxisomes as the cargo and its delivery to the autophagic machinery for pexophagy (Farré et al., 2008). It has been shown in yeast that PpAtg9 is essential for the formation of sequestering membranes that engulf the peroxisomes for degradation within the vacuole (Chang et al., 2005). Upon the onset of micropexophagy, PpAtg11 recruits PpAtg9 to the perivascular structure, which acts as the site of formation of the sequestering membrane presumably by causing segmentation of the vacuole. These membranes subsequently engulf the peroxisomes and eventually fuse with the help of PpAtg1 and PpVac8 to incorporate the peroxisomes into the vacuole for degradation (Chang et al., 2005). In contrast, during macropexophagy, peroxisomes are sequestered primarily by inclusion within the newly formed membranes. Subsequently, the peroxisome-containing pexoautophagosome fuses with the vacuole to deliver its cargo. In the light of the difference in the sequestering mechanism between micropexophagy and macropexophagy, the former process requires a higher level of ATP. Different types of peroxisome degradation systems have been found in H. polymorpha (Manivannan et al., 2013): (1) glucose-induced selective pexophagy serves to degrade peroxisome-containing enzymes that are redundant for growth, and (2) under nitrogen starvation conditions, peroxisomes are degraded by nonselective microautophagy (Bellu and Kiel, 2003). Peroxisome degradation occurs during normal vegetative growth of the yeast cells to continuously rejuvenate this organelle (Aksam et al., 2007). A recent study by Manivannan et al. (2013) indicates that protein aggregate-containing peroxisomes undergo fission/degradation. They obtained this information by introducing protein aggregates in the organelle matrix. Production of a mutant variant of peroximal catalase results in the formation of large intraorganellar protein aggregates. It is known that protein aggregates are toxic in eukaryotic cells, and their accumulation causes the generation of ROS. The removal of such peroxisomes is an example of quality control process. Pex11 proteins are thought to be actively involved in the recruitment and/or assembly of the peroxisomal fission (Schrader et al., 2012). Asymmetric fission results in the formation of small and large organelles. According to Manivannan et al. (2013), small organelles are preferentially degraded by pexophagy; however, according to Veenhuis et al. (1983), larger peroxisomes are preferentially degraded. These two studies were carried out under different conditions. As stated earlier, pexophagy has been extensively studied in the methylotrophic yeast P. pastoris that is capable of growth on methanol as a sole source of carbon and energy. Peroxisomes can be rapidly and selectively degraded when methanol-grown yeast cells are placed under conditions of repression of methanol metabolism (e.g., glucose) by a process termed micropexophagy (van Zutphen et al., 2008). Degradation of peroxisomes is also observed when yeast cells are placed in an ethanol medium, termed macropexophagy. In other words, micropexophagy is induced by glucose, while macropexophagy by ethanol. The micro- and macropexophagy pathways are morphologically similar to the micro- and macrophagy pathways, respectively. The introduction of these two pathways depends on the carbon source in the methylotrophic yeast (Ano et al., 2005).


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On the other hand, phthalate esters can cause a marked proliferation of peroxisomes. It has been demonstrated in the yeast that protein trafficking, lipid trafficking, or both as directed by Sar1p are essential for micro- and macropexophagy (Schroder et al., 2008). Stasyk et al. (2008) have presented methods for monitoring peroxisome status in the yeast. Autophagic degradation of peroxisomes can be monitored with electron microscopy as well as by using biochemical assays for peroxisome markers. Several types of membrane dynamics during pexophagy can be visualized simultaneously under live cell imaging. During micropexophagy, peroxisomes are incorporated directly into the vacuole by invagination. Finally, it can be deduced from the above discussion that the process of pexophagy in the Cvt pathway with regard to its turnover, autophagic adaptor proteins, and peroxisome engulfment is more complex than that described above. For example, Grunau et al. (2011) have discovered the PtdIas3P-synthesizing activity in peroxisomes of S. cerevisiae and lipid kinase Vps34p is associated with peroxisomes during their biogenesis. Although Vps34p is involved in such biosynthesis, this kinase is not essential for optimal peroxisome biogenesis. It seems that Vps34p-containing complex I and a subset of PtdInos3p-binding proteins are required for the regulated degradation of peroxisomes.

Reticulophagy Reticulophagy is responsible for the selective sequestration of portions of the ER with associated ribosomes. ER is a highly complex organelle, composed of a single continuous phospholipid membrane and flattened peripheral sheets with associated ribosomes. Almost all eukaryotic cells contain a discernible amount of ER because it is needed for the synthesis of plasma membrane proteins and proteins of the extracellular matrix. Although detoxification of drugs, fatty acid and steroid biosynthesis, and Ca2+ storage occur in the smooth ER, most of the folding and posttranslational processing of membrane bound and secreted proteins take place in the ER. Ribosomes present free in the cytosol mainly translate cytoplasmic proteins, whereas ribosomes associated with the ER membrane synthesize proteins that are secreted or reside in one of the organelles of the endomembrane system. As these newly synthesized proteins are cotranslationally translated into the ER, a substantial proportion of these proteins remains located in this compartment (Cebollero et al., 2012). Both autophagy-dependent and autophagy-independent systems are involved in reticulophagy. Accumulation of excess membrane proteins on the aberrant ER induces ER stress and blocks the transportation of these membranes to the lysosome. Recently, it was reported that the conserved Ypt/Rab GTPases regulate reticulophagy (Lipatova et al., 2013). A Ypt/ Rab GTPase module consisting of the Tris85-containing TRAPP111 GEF, Yptl, and the Atgll effector regulates shuttling of tagged, overexpressed, and misfolded proteins from the ER to the autophagic pathway (Lipatova et al., 2013). It is known that these GTPases regulate trafficking between cellular components. These proteins are stimulated by guanine-nucleotide exchange factors (GEFs) to recruit multiple effectors, which mediate all vesicular transport events (Segev, 2001). It is also known that Ypt regulates ER-to-Golgi transport and autophagosome formation (Chua et al., 2011). Indeed, Ypt has multiple roles. The ER stress signal along with other signals (e.g., oxidative signal) is involved in autophagy. The former is involved in membrane formation and fusion, including autophagosome formation, autophagosome–lysosome, and degradation of


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intraautophagosomal contents by lysosomal hydrolases. ER stress is also involved in amplifying ROS production (Rubio et al., 2012). This study indicated that apical ER photodamage in murine fibrosarcoma cells generated ROS via mitochondria, which contributed to the processes of reticulophagy. UPR is an intracellular signaling triggered by the ER stress. ER stress occurs under various physiological and pathological conditions where the capacity of the ER to fold proteins becomes saturated, for example, as a response to incompetent or aggregation prone proteins, Ca2+ flux across the ER membrane, glucose starvation, or defective protein secretion or degradation (Hoyer-Hansen and Jaattela, 2007). Glucose starvation results in reduced protein glycosylation, and hypoxia causes reduced formation of disulfide bonds. ER stress resulting from the accumulation of unfolded or misfolded proteins threatens cell survival and ER to nucleus signaling pathway; this pathway is called the UPR. UPR reduces global protein synthesis and induces the synthesis of chaperone proteins and other proteins, which increase the ER capacity to fold its client proteins (Hoyer-Hansen and Jaattela, 2007). To prevent the accumulation of misfolded polypeptides in the ER, chaperone proteins are thought to assist in the folding of the nascent polypeptides or recognizing the misfolded proteins and mediate their refolding (Braakman and Bulleid, 2011). However, under certain conditions, unfolded proteins accumulate in the ER. At least two interconnected mechanisms are available to cope with such undesirable protein aggregation: (1) the UPR and (2) the ERAD (Bernales et al., 2006b; Römisch, 2005). The UPR signaling is transduced into cytoplasmic and nuclear actions aimed at increasing the protein folding capacity of the ER and eliminating the proteins that remain misfolded and accumulated in the ER. UPR also initiates inhibition of general translation and upregulation of genes encoding ER chaperones and components of the ERAD machinery (Cebollero et al., 2012). The ERAD, in turn, recognizes misfolded proteins and translocates them into the cytoplasm where they are degraded by the UPS. When the function of the ER is not restored, it may lead to cell death by apoptosis or autophagy depending on the cell type and the stimulus (Momoi, 2006). In the absence of or inefficient reticulophagy, misfolded or unfolded proteins accumulate on the ER membranes; examples of such proteins are: α-synuclein (PD), amyloid protein (AD), htt protein (HD), FUS protein (amyotrophic lateral sclerosis), and PrP (prion disease). These accumulated proteins on the ER membrane are implicated in neurodegenerative diseases. Under such circumstances, cells fail to maintain protein homeostasis (proteostasis) and elicit UPR. UPR serves to attenuate protein translation and increase protein refolding or degradation.

Ribophagy Selective degradation of ribosomes is termed ribophagy. Ribosomes are essential components of all cells and constitute the translation engine of the cell. The protein synthesis is catalyzed by ribosomes, which are composed of large complexes of RNA and protein molecules. Each ribosome is composed of one large subunit (60S) and one small subunit (40S) in eukaryotes, while prokaryotic ribosomes are made up of 50S and 30S subunits. Although these two types of ribosomes differ in size and amount in eukaryotes and prokaryotes, both have the same function. Before protein synthesis can begin, the corresponding mRNA


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molecule must be produced by DNA transcription. This is followed by the binding of the small subunit to the mRNA molecule at a start codon that is recognized by an initiator tRNA molecule. Then the large subunit binds to complete the ribosome and initiate the elongation phase of protein synthesis. Ribosome turnover occurs both under normal conditions and under starvation. Under, normal nutrient-rich conditions, large amounts of ribosomal subunits are assembled, which raises the possibility for the need of the removal of excess ribosomes in response to changing environmental conditions (Bakowska-Zywicka and Tyczewska, 2009). Ribophagy pathway could also target defective ribosomes under normal growth conditions (Cebollero et al., 2012). This is a quality control function. It is also known that autophagy of ribosomal proteins is involved in antibacterial function. Some information on the pathway of normal ribosome turnover, especially the role of rRNA decay, is available. Arabidopsis RNS2 (a conserved ribonuclease of the RNAse T2 family) is necessary for normal decay of rRNA (Macintosh and Bassham, 2011). The absence of RNS2 results in longer-lived rRNA and its accumulation in the yeast vacuoles and ER, showing constitutive autophagy. This evidence supports the concept that RNS2 participates in a ribophagy-like mechanism that targets ribosomes for recycling under normal growth conditions (Macintosh and Bassham, 2011). Regarding the role of ribophagy during starvation, cells are subjected to energy shortage and need to save available energy. The beginning of the construction of ribosomes in the cell nucleus and the subsequent translation they carry out require considerable energy. Therefore, cells need to save energy, which is accomplished by removing ribosomes and terminating the translation and protein synthesis. Ribophagy begins by separating the two subunits of a ribosome. It has also been suggested that Ubp3/Bre5 (discussed later) regulates different types of selective autophagies during starvation (Beau et al., 2008). It is important to identify the genes required for ribophagy. Kraft et al. (2008) indicated the involvement of two proteins, ubiquitin-specific protease 3 (Ubp3) enzyme and Ubp3-associated cofactor (Bres) in the selective degradation of ribosomes, but not for bulk autophagy. They also indicated that ribophagy affects the entire 60S subunit, but not the 40S subunit, suggesting differential degradation of large and small subunits. These authors, furthermore, demonstrated the involvement of Atg1 and Atg7 in the transport of ribosomes to the vacuole in the yeast S. cerevisiae. It also has been reported that the Ubp3/Bre5 complex interacts with Atg19 protein and modulates its ubiquitination (Baxter et al., 2005). It is concluded that ribosome degradation relies on both ribophagy and nonselective autophagy. The evidence presented here and from other studies confirms a cross talk between selective autophagy and ubiquitin-dependent processes. The majority of cellular proteins and most other cell components are eventually degraded and recycled in a cell either by autophagy or the ubiquitin-proteasome pathway or by a combination of these two systems. In fact, there is a connection between autophagy and ubiquitin modification and destruction by the proteasome pathways of protein degradation.

Xenophagy The successful invasion of the host cell by the pathogenic microorganisms depends on their ability to subvert intracellular signaling to avoid triggering immune response of the cell. The host cell, under normal conditions, possesses pathways (xenophagy) that protect it


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from infection. Posttranstional modifications (ubiquitination) play a role in the activation of xenophagy. A link between ubiquitination and the regulation of autophagy has been established (Dupont et al., 2010). It is also known that p62 proteins target protein aggregates for degradation via autophagy. Pathogens, however, have developed mechanisms that subvert defense systems of the cell (xenophagy), replicating themselves. M. tuberculosis, for example, prevents inflammasome activation (Master et al., 2008). Other mechanisms involve the interference with the host cell ubiquitination, membrane injury, and impairment of SUMOylation.

Zymophagy Pancreatic acinar cells are highly differentiated cells that synthesize and secrete digestive enzymes into the pancreatic juice. These digestive enzymes are initially produced as inactive enzymes (zymogens) and stored in zymogen granules until exocytosis. These granules can be harmful if activated prematurally because the release of these enzymes can hydrolyze tissue parenchyma, resulting in pancreatitis (Grasso et al., 2011). VMP1 interacts with Beclin 1/Atg6 through its hydrophilic C-terminal region, which is necessary for early steps of autophagosome formation. Thus, the involvement of VMP1 is implicated in the induction of autophagy during this disease. VMP1 also interacts with the ubiquitin-specific proteases (USPs), indicating close cooperation between the autophagy pathway and the ubiquitin machinery required for selective autophagosome formation (Grasso et al., 2011). Ubiquitylation and ubiquitin-receptors such as p62 (SQSTAM1) play a part in vesicular traffic in pancreatitis. In fact, a VMP1-USP4-p62 molecular pathway is involved in mitophagy. As explained earlier, if zymogen granules prematurally release the digestive enzymes in the acinar cells, the result could be pancreatitis. Under normal physiological conditions, selective autophagy (zymophagy) degrades the activated zymogen granules, avoiding the release of digestive enzymes into the cytoplasm and thus preventing further trypsinogen activation and cell death. In other words, zymophagy has a critical function in secretory homeostasis and cell response to injury by selective degradation of altered secretory granules in acute pancreatitis. In conclusion, zymophagy protects the pancreas from self-digestion. It is a selective form of autophagy, a cellular process to specifically detect and degrade secretory granules containing activated enzymes before they can digest the organ (Vaccaro, 2012). Zymophagy is activated in pancreatic acinar cells during pancreatitis-induced vesicular transport alteration to sequester and degrade potentially deleterious, activated zymogen granules.

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2 Methods for Measuring Autophagosome Flux— Impact and Relevance Andre Du Toit, Jan-Hendrik S. Hofmeyr and Ben Loos O U T L I N E Introduction 92 Measuring Autophagic Flux—A Slope Rather Than a Column

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Summary, Conclusion, and Future Outlook 101 Acknowledgments 102 References 102

Modeling the Autophagy System—Key Determinants Characterized by Rates 98

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Autophagy is an essential protein degradative pathway that maintains cellular and metabolic homeostasis. Autophagy dysfunction is associated with many human pathologies and impacts directly on the susceptibility of the cell to undergo cell death. Although we have learnt a great deal about the molecular machinery that governs the autophagic process, an accurate capturing of especially the dynamic rearrangement of membranes and degradation of cargo that form part of the autophagy machinery remains challenging, and consequently the translation of autophagy control to the clinical environment has remained poor. In this chapter we highlight the recent advances in the fields of measuring and modeling autophagic flux and the entire autophagy system. We emphasize the dynamic nature of the autophagy system itself, the connection between autophagy and the metabolic status of the cell, and we suggest an assessment approach that allows the integration of cargo and machinery fluxes. Finally, by discussing control analysis and a systems approach as uniquely positioned tools, we underscore the current knowledge base of the autophagy system and its models as well as key-associated metabolic parameters and molecular checkpoints that intricately link to cellular fate. In doing so, we hope to bring about clarity on required measuring approaches, to better assess and interpret autophagic flux dysfunction and systems failure, yielding future advances in precisely controlling and manipulating the autophagic process for therapeutic purposes. M.A. Hayat (ed): Autophagy, Volume 11. DOI: http://dx.doi.org/10.1016/B978-0-12-805420-8.00002-0

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INTRODUCTION Autophagy is an essential protein degradative pathway that maintains cellular and metabolic homeostasis. Three types of autophagy exist: macroautophagy, microautophagy, and chaperone-mediated autophagy, in which macroautophagy being thought to be primarily responsible for the degradation of the majority of intracellular proteins and is simply referred to as autophagy hereafter. Autophagy has become an immensely hot field in biology. This degradation process for long-lived proteins has received major attention in the last two decades and continuous to grow in impact. Many landmarks in the autophagy research have been reached, with more than 50 years having passed since the coining of the term “autophagy”. However, although we have learnt a great deal about the molecular machinery and the regulatory system that governs the autophagic process (Feng et al., 2014), and although we increasingly understand the role of dysfunctional autophagy in disease, the translation of autophagy control into the clinical environment has been challenging. Many questions remain to be answered and an essential aspect that emerges as focus point centers on the development of robust systems and tools to assess the autophagic process and its dynamic machinery accurately. Although the volumes of available tools and methodologies to measure the entire autophagy process are growing rapidly, building some of the most comprehensive (Klionsky et al., 2016) and research community–driven (Klionsky et al., 2016) guidelines for the use of suitable assays, equally so emergent are the articles indicating cautions, pitfalls, and recommendations (Gómez-Sánchez et al., 2015). It becomes clear that the accurate capturing of especially the dynamic rearrangement of autophagosomes and degradation of cargo that form part of the autophagy machinery remains challenging. In this context one of the central discussions that continues to emerge hand in hand with the search for improved assays to measure autophagy (Rubinsztein et al., 2009) is the relationship between concentrations of pathway intermediates and flux through the autophagic pathway. It becomes increasingly clear that not only much can be learnt from the field of metabolism (Meijer, 2009), where correlation between metabolites, rates, and fluxes has been known for decades, but also much can be directly applied to better capture, quantify, and parameterize the autophagic system and its flux (Tsvetkov et al., 2013; Koga et al., 2011; Loos et al., 2014). In this chapter we highlight the recent advances in the fields of measuring and modeling autophagic flux and model systems of the autophagy system. We discuss the role of control analysis in autophagy, so as to better discern the regulation and control of its system in the context of candidate disease states where autophagic flux is dysfunctional or deviated. Finally, we highlight the current knowledge of the autophagy proteome, the emerging metabolic checkpoints, and intricate links to cellular fate. In doing so, it is hoped not only to better reveal the dynamic nature of the autophagy system itself, the connection between autophagy and the metabolic status of the cell, but also to suggest an assessment approach that allows the integration of cargo and machinery flux, i.e., autophagosome flux alike, allowing to better quantify autophagic flux dysfunction and systems failure. This may assist in yielding future advances in more effectively and precisely controlling and manipulating the autophagic process for therapeutic purposes.


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MEASURING AUTOPHAGIC FLUX—A SLOPE RATHER THAN A COLUMN Reliable and quantitative assays to measure autophagy and its dynamics in vitro and in vivo are essential (Klionsky et al., 2016). It is now largely accepted that the level of specific autophagy pathway intermediates, such as LC3-II or p62 protein (Meijer, 2009), or the autophagosomal pool size (Loos et al., 2014) does not necessarily represent flux through the autophagic pathway. Care in the interpretation of results as well as in the citation of literature needs to be taken, since autophagic flux has not always been measured properly, primarily when the understanding of the autophagic system was still in its infancy. For example, an increase in LC3-II levels may have been frequently interpreted as an induction or activation of autophagy, while in reality the complete opposite may be true. Autophagic flux, i.e., the protein degradation rate through macroautophagy, is assessed best with techniques that are aligned with the requirement of assessing a rate, i.e., the rate of autophagosome formation or the rate of autophagosome degradation. This demands the fulfillment of two crucial aspects: first, being able to measure the pathway intermediates themselves accurately and second, to apply the existing measuring tools in a manner that allows the quantification of the synthesis and/or degradation rate. The former is very well established, and many powerful tools and assays exist (Klionsky et al., 2016), primarily based on Western blot analysis and high-end microscopy to assess the identity of early and late autophagic compartments, respective protein levels, the morphology of autophagosomes, autophagolysosomes, and lysosomes at high resolving power, even in a three-dimensional context (Ylä-Anttila et al., 2009). The latter, however, requires the use of selective tools and an experimental environment that allow an assessment of the pathway intermediates in time, with the inclusion of carefully selected pathway inducers and inhibitors. This is an important and often overlooked requirement, since the desired outcome of assessing autophagy is a quantitative measure of the rate of flow through the pathway. The autophagic process may be in a steady state, where the pathway intermediates or entities that are produced and degraded, are constant, or in a transition toward a new steady state, either being enhanced or being blunted. Hence the identification of the steady-state flux J of a given cellular system is a major prerequisite (Loos et al., 2014) to characterize protein degradation through autophagy. With the generation of a transgenic mouse model expressing the fluorescent marker LC3, it became for the first time clear not only that the various mammalian tissues in fact perform protein degradation through autophagy, but also that this process occurs at different levels. Not only did the pathway intermediate LC3 show major discrepancies in its expression levels between, for example, the brain, the myocardium, or liver, suggesting major differences in both lipidated and nonlipidated LC3, but also was the response to enhance autophagy through 24 h nutrient starvation distinct (Mizushima et al., 2004). Even within the same tissue, such as skeletal muscle, a differential starvation response was observed, highlighting the close relationship between autophagy, metabolite generation, and cellular metabolism. Finally the duration of an enhanced or changed autophagic activity was distinct, indicating differential, tissue-specific autophagic capacities, and temporal changes in feedback mechanisms. These data indicated for the first time clearly that a quantification system


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beyond standard morphometric analysis is required, and that even immunogold electron microscopy, although powerful in resolving specific structures of the autophagic machinery, is ill equipped in reporting on the rate of autophagosome generation and degradation. Although many studies have been made to measure autophagic flux in vitro as well as in vivo and ex vivo, the exact numerical identity of the steady-state flux as well as that of an enhanced autophagic flux upon its induction in mammalian cells and tissues remains currently unknown. Why is that so? It is largely accepted that the amount of LC3-II protein per se correlates best with the amount of autophagy membranes (Zois et al., 2011), however, by no means does this quantity per se correlate with autophagic flux. Western blot analysis, used to measure the amount of LC3-II protein in the presence and absence of inhibitors that prevent the degradation of LC3 protein, is widely used as a functional reporter on autophagy (Rubinsztein et al., 2009). Such “autophagometer” has brought tremendous clarity to the interpretation of autophagy intermediate protein levels and has accelerated the field of autophagy research. However, although highly valuable to assess autophagy, it measures best the flux status, i.e., whether autophagic flux is present, enhanced, and decreased at the time of intervention (Rubinsztein et al., 2009). Some experiments have shown very elegantly the important insights gained when doing so (Rubinsztein et al., 2009), allowing to report on the autophagic flux status in retina (Esteban-Martínez and Boya, 2015), the myocardium (Iwai-Kanai et al., 2008), or skeletal muscle (Ju et al., 2010) or assessing the response of tissues to starvation (Zois et al., 2011). Usually, inhibitors such as bafilomycin A1, colchicine, chloroquine, vinblastine, or leupeptin are being used to inhibit the functional fusion between autophagosomes and lysosomes (Esteban-Martínez and Boya, 2015; Ju et al., 2010; Iwai-Kanai et al., 2008), and basal levels of autophagy as well as the effects of an intervention are being assessed in that manner. Nevertheless, merely the flux status can be reported in that manner, since Western blot analysis is not strongly aligned with the requirements of measuring the change of pathway intermediates in time (Fig. 2.1). This makes it difficult to analyze autophagy in a manner that would allow the dissection of differences between cell lines and tissue types, and to this date not “flux database” exists, that would suggest basal fluxes or enhanced fluxes in a standardized manner. Often a combination of techniques such as Western blot analysis, electron- and fluorescence microscopy as well as flow cytometry are being performed, with varying degrees of morphometric analyses, to enhance confidence in a given flux status. The predominant method, however, remains immunoblotting, and powerful literature exists to interpret data derived in that manner (Jiang and Mizushima, 2015; Gómez-Sánchez et al., 2015). Fundamental advances have been made in measuring autophagic flux by using fluorescence-based techniques and/or photoswitchable or photoactivatable proteins, in a live cell imaging environment (Tsvetkov et al., 2013; Koga et al., 2011; Loos et al., 2014), where the changes of autophagy intermediates after the use of above-mentioned inhibitors are plotted in time. In sharp contrast to above methods, here, the change of autophagy intermediates is expressed as either a progress curve of a mean lifetime in hours (Tsvetkov et al., 2013), the number of punctae per cell per time, the mean fluorescence intensity in time (Koga et al., 2011), or the total autophagosome pool size nA in time (Loos et al., 2014). Such an approach suggests a defined degradation rate per time unit, strongly aligned with the requirement of assessing fluxes. When doing so, data points that are usually analyzed and displayed in


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Measuring Autophagic Flux—A Slope Rather Than a Column

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FIGURE 2.1 (A) Measuring autophagic flux. Western blot analysis is not strongly aligned with the requirements of measuring the change of pathway intermediates in time. (B) In the presence and absence of relevant autophagosomal/lysosomal inhibitors, merely the flux status, i.e., unchanged, increased, or decreased autophagic flux, can be reported. (C) Autophagic flux can, in theory, be measured not only by assessing the (increasing) slope of LC3-II signal in time after the use of lysosomal inhibitors such as bafilomycin (I), acting downstream in the autophagy process, but also by measuring the (decreasing) slope of LC3-II signal after the application of synthesis inhibitors (II), such as 3-MA, acting upstream on the autophagy machinery. (D) The resultant slopes of both measures when plotting the progress curves would, in theory, be equal, suggesting the same flux JI and JII, assuming that the autophagy system is in steady state, and assuming that a basal protein degradation rate exists in the measured system.

column graphs of units such as “LC3/actin intensity,” “relative fold changes to control,” “volume of autophagic vacuoles/volume of cytoplasm,” “Nr of GFP-punctae/area” become measurable over time, presented as progress curves with slopes of defined characteristics. Therefore, the representation of an autophagic flux status becomes truly represented as the protein degradation rate through autophagy or chaperone-mediated autophagy, indicated as a distinct cell- and context-dependent slope. It is hence clear that autophagic flux, the degradation rate of protein cargo through autophagy, is dependent on both the autophagosome formation rate as well as the autophagosome degradation rate. Therefore, autophagic flux could, in theory, be measured not only by assessing the (increasing) slope of LC3-II signal in time after the use of lysosomal inhibitors, acting downstream in the autophagy process (Loos et al., 2014) but also by measuring the (decreasing) slope of LC3-II signal after the application of synthesis inhibitors, acting upstream on the autophagy machinery.


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The resultant slopes of both measures, assuming that the autophagy system is in a steady state and assuming that a basal protein degradation rate existed in the measured system, will be equal (Fig. 2.1). A major advantage of such an approach is not only that it measures autophagic or CMA flux most accurately, but also that it can concomitantly be used to discern between specific cargo fluxes and the machinery, i.e., autophagosome flux. This is of importance, since not only it is likely that every cargo is dependent on a defined set of enzyme activities that govern its cargo flux, but also it is evident that the levels of cargo protein expression may change in time, and be dependent on autophagically generated amino acids, hence the autophagic flux itself (Sahani et al., 2014). Taken together, it becomes clear that both the autophagy machinery, i.e., autophagosome flux, (Loos et al., 2014) as well as specific cargo flux (Koga et al., 2011; Tsvetkov et al., 2013) may be assessed separately, and it is anticipated that these fluxes are not always the same.

QUANTIFYING THE AUTOPHAGIC FLUX DEVIATION WITH PRECISION One may ask, is it really crucial to be able to quantify autophagic flux, its basal levels, and its deviation in pathology in such a precise manner? Would an estimate of an increased or decreased autophagic activity not be sufficient to understand the autophagic pathway in its complete and dynamic nature? Recent landmark articles have indicated that autophagy plays a major role in metabolism (Mizushima and Klionsky, 2007) and in the onset of many diseases (Mizushima et al., 2008). The absence of basal autophagy is not compatible with live and the alterations in plasma amino acid levels postbirth suggest a major impact of protein degradation through autophagy on cellular metabolism (Komatsu et al., 2005; Kuma et al., 2004). Neurons degenerate and die when basal autophagy is being suppressed, as has been shown in mice deficient for Atg5 (autophagy-related 5) (Hara et al., 2006) or Atg7 (Komatsu et al., 2006). Here ubiquitinated proteins begin to aggregate in the neurons of the cortex, the hippocampus, and the cerebellum (Hara et al., 2006). Although it is now largely accepted that neurons are characterized by a particularly efficient autophagic system with a high protein clearance rate (Nixon and Yang, 2011), the exact autophagic flux, however, as described in some scenarios at a single-cell level (Tsvetkov et al., 2013; Koga et al., 2011; Loos et al., 2014) under basal conditions, in the various subtypes of neurons and astrocytes remains currently unknown. Although it is now clear that autophagy dysfunction is directly linked to a number of neurodegenerative diseases and that distinct types of dysfunctions exist within the autophagic process (Wong and Cuervo, 2010; Nixon and Yang, 2011), to what extent autophagic flux deviates from basal levels is very much unclear. Despite the notion that autophagic flux is gradually inducible (Wong and Cuervo, 2010), we remain unable to quantify autophagic flux ranging from physiologic to pathologic levels. The precise characterization of mTOR or Beclin-dependent and Beclin-independent autophagy modulators remains therefore a major challenge (Zhang et al., 2007). The consequences thereof are significant. In the case of Alzheimer’s disease, for example, it is known that the candidate aggregate-prone proteins, amyloid-β, and tau are targeted by the autophagic machinery and can both be cleared by enhancing autophagic flux (Caccamo et al., 2010). It is, however, not known to what extent autophagic flux deviates in a given


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model of Alzheimer’s disease and to what degree a pharmacological intervention is able to offset the pathological flux deviation. This is further substantiated by characteristic mutations such as PS-1, which lead to a defect in the acidification process of lysosomes, thereby affecting autophagosomal degradation rate (Lee et al., 2010). However, how much the autophagic flux is blunted remains unclear. Moreover, the spatiotemporal autophagic flux profile in the pathogenesis of neurodegeneration remains largely unclear, further complicating such an assessment. This makes any treatment approach, even when using FDA-approved drugs to modulate autophagy, a major challenge. Similarly, although it is known that α-synuclein can be targeted by the autophagic machinery (Wong and Cuervo, 2010; Friedman et al., 2012), quantitatively, the relationship between autophagic flux and α-synuclein cargo degradation remains unclear. Finally the most intriguing scenario is evident in Huntington’s disease. It is apparent that autophagosome dynamics are regulated by huntingtin (Wong and Holzbaur, 2014) and that the mutated protein is targeted and can be effectively cleared by enhancing autophagic flux (Sarkar et al., 2009). In addition, however, Huntington’s disease is characterized by a specific autophagy malfunction, which results in the inability of autophagic vacuoles to recognize cytosolic cargo (Martinez-Vicente et al., 2010). Hence, autophagy per se is operational, autophagic vacuoles form normally or even at enhanced rates, however, autophagosome flux operates here independent and unsynchronized from the cargo flux. These findings crucially stress the relevance of measuring and discerning between cargo and machinery flux, preferably for both autophagy as well as chaperone-mediated autophagy (Fig. 2.2). This notion is supported by the identification of specific cargo receptors and adaptors (Lamark et al., 2009), characterized by an LIR motif that is interacting with ATG8 family proteins, further pointing toward the possibility to assess the degradation rate of specific cargo (Weidberg et al., 2011) and candidate aggregate-prone proteins. Finally the importance of accurately quantifying autophagic flux and its deviation from healthy tissue becomes clear in the context of tumor cells. First, cancer cells are often characterized by a heightened basal autophagic flux (Xie et al., 2013). Such an increased autophagic proficiency often manifests in a more aggressive tumor cell phenotype. However, the extent of the autophagic flux increase, compared to healthy tissue, is largely unclear. This becomes further complicated by the fact that the autophagic proficiency may change in the course of disease progression or tumor transformation, being of stable or of temporary nature (Galluzzi et al., 2015). Moreover, the metabolic microenvironment across a tumor tissue may be distinct, leading to differential autophagic fluxes within distinct areas of the tissue (Rangwala et al., 2014). In addition, specific mutations, that manifest in, for example, enhanced RAS-MEK signaling, are in particular characterized by heightened autophagic flux as well as an increased autophagy dependency or “autophagy addiction” (Yang et al., 2011). Also in terms of autophagy modulation to sensitize cancer cells to chemotherapy, it becomes evident that both the enhancement and the inhibition of autophagy may lead to apoptosis onset. A combination treatment using mTOR inhibitors and lysosomal deacidifying agents, such as hydroxychloroquine concomitantly, may even suppress tumor growth significantly, compared to the single modulators (Xie et al., 2013). Taken together, it becomes clear that the extent of autophagy modulation, as described above, discerning autophagosome flux and cargo flux (Tsvetkov et al., 2013; Koga et al., 2011; Loos et al., 2014) in candidate tissues with known autophagy pathology, remains largely unknown, making an accurate autophagy control challenging.


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(A)

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FIGURE 2.2 Relevance of measuring and distinguishing between autophagic cargo flux and autophagosome flux for both autophagy (A) as well as chaperone-mediated autophagy (C): (A) Autophagy may be operational, autophagic vacuoles form normally; (B) however, autophagosome flux may also operate independently and desynchronized from the cargo flux, as distinct for the cargo recognition failure in Huntington’s disease.

MODELING THE AUTOPHAGY SYSTEM—KEY DETERMINANTS CHARACTERIZED BY RATES The above literature makes clear that autophagy impacts profoundly on cellular metabolism. Autophagy is a strictly regulated mechanism that is integrated not only with the metabolism of the whole cell but also with the metabolic cost of the cell. Although morphometric as well as biochemical indices that characterize the autophagy pathway are immensely powerful, modeling studies are highly attractive as they allow a better integration and connect of the underlying molecular mechanisms that drive the autophagy machinery, allowing for the identification of causal relationships between autophagy and important intracellular parameters (Moore et al., 2006). Here we summarize the emerging


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most crucial parameters that connect autophagic flux with the cellular metabolic sensing and energetic demand. It becomes clear that autophagic flux and the pathway intermediate pool sizes cannot be considered in isolation, but must be integrated with metabolic parameters, most of which are characterized by inherent steady-state concentrations as well as rates of synthesis or activity (Fig. 2.3A). Rates of respiration, rates of synthesis and degradation, as well as rates of organellar trafficking and translocation (McVeigh et al., 2006) all contribute to the description of the autophagy system, and highlight not only their dynamic relationship to one another (Fig. 2.3A) but also their response to cellular stress (Moore et al., 2006). To understand the autophagy system, the individual system parameters need to be carefully mapped out and their relationship to one another assessed. The autophagy system is characterized by a unique regulation system that integrates cellular metabolism, amino acid availability, and the current energetic state (Loos et al., 2013). mTOR on the one hand regulates autophagy through direct phosphorylation of the downstream target Ulk1, thereby disrupting the interaction between AMP-activated kinase (AMPK) and Ulk1 and preventing autophagy induction (Kim et al., 2011). AMPK is able to directly phosphorylate Ulk1, particularly when a poor energetic charge, i.e., a decrease in intracellular ATP is being sensed (Kim et al., 2011). Moreover, it also known that the rate of protein degradation through autophagy decreases profoundly with a drop in intracellular ATP (Schellens et al., 1988). ATP demand is primarily determined by a hierarchy of ATP-consuming processes, of which protein synthesis and ATPase activities, such as the NA+/K+ or H+ ATPase, are considered as the top scorers in ATP consumption (Buttgereit and Brand, 1995). This is of importance, since autophagic flux does affect not only amino acid availability and thereby metabolism and ATP availability but also protein degradation activity, especially when being controlled in an mTOR-dependent fashion (Fig. 2.3A). Such an approach may allow to better dissect, how a change in, for example, ATP demand, through the inhibition of a NA+/K+ ATPase may impact on autophagic flux (Liu et al., 2013). Moreover, mTOR is stimulated by amino acids, which promote the translocation of mTOR to the lysosomal membrane (Zoncu et al., 2011). Autophagic flux therefore impacts on the amino acid pool size, which in turn affects mTOR localization and activity. mTOR translocation to the lysosomal membrane enables thereby favorable positing, in close proximity to the permeases that drive amino acid release at the lysosomal membrane (Yang and Klionsky, 2007). In addition, functional mTOR-mediated amino acid sensing requires the vacuolar H+ ATPase, suggesting that not only lysosomal pool size nL (Fig. 2.3A) but also lysosomal function determines accurate mTOR-mediated sensing and subsequent autophagy regulation (Zoncu et al., 2011). Particularly leucine and glutamine (Jewell et al., 2015) have been suggested in this context to differentially regulate mTOR activation. One approach to gain a system-level understanding of autophagy is to build mathematical models and simulations based on biochemical and morphometric indices that in turn reconstruct autophagy dynamics at high time resolutions. Defining the compartments and pool sizes with all autophagy-related rates highlights not only autophagy selectivity but also quality, described as a measurable index (Han et al., 2014). This allows the introduction of selected quantitative indices and reveals a specific quantitative interpretation (Han et al., 2014), leading to a better definition of autophagy activation and a clearer quantitative description of the time evolution of particular autophagy-related parameters (Han et al., 2012). In this manner a theoretical study has revealed an oscillatory behavior of intracellular


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2. Methods for Measuring Autophagosome Flux—Impact and Relevance (A)

Nutrient status

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mTOR-independent autophagy regulation

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FIGURE 2.3 (A) Hypothetical conceptual model schematic showing the autophagy system with its key components and associated regulatory parameters, most of which are characterized by inherent steady-state concentrations as well as rates of synthesis or degradation. (B) Hypothetical model depicting cellular autophagic flux and proteotoxicity during disease progression from a healthy (1) to a dying (4) cellular state. Proteotoxicity onset, in the presence (2a) or absence (2b) of an enhanced and adaptive autophagy response, with a resultant level of nonadaptive (3a) and adaptive response in proteotoxicity (3b).


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autophagosomal and autophagolysosomal pool sizes, suggesting an intrinsic system behavior that is interrelated with ATP, amino acid, and protein dynamics (Han et al., 2012). This may not only describe the dynamic relationship of the contributing parts of the autophagy system better (Fig. 2.3A), but in theory also allows the autophagosome flux to be distinguished from disease-specific cargo flux (Han et al., 2015). Another approach to better describe the autophagic system, autophagosome, and cargo flux is based on the framework of supply–demand analysis, which affords understanding of the steady-state behavior, control and regulation of autophagy (Loos et al., 2014; Hofmeyr and Cornish-Bowden, 2000). Here autophagosome flux and cargo flux can be related quantitatively to the elasticities of supply and demand (Hofmeyr and Cornish-Bowden, 2000). By introducing finely controlled perturbations to a component of the system and measuring the response in the steady-state variables, the flux and concentration-control coefficients of that component can be determined (Cornish-Bowden and Hofmeyr, 1994). Moreover, by varying particular parameters of the system incrementally, the rate characteristics of supply of and demand for autophagosomes can be constructed. Rate characteristics are useful because not only they describe the steady-state behavior of the supply and demand blocks over a wide range of autophagosome concentrations, but they also allow the calculation of the supply and demand elasticity coefficients, from which the flux-control distribution between supply and demand can be calculated. Together with above discussed means to measure autophagosome and cargo flux more precisely, such an approach may be very powerful for finding the locus of the control over autophagic and cargo fluxes in both normal and diseased conditions. It becomes clear that modeling the autophagy system in its entirety allows for a far better understanding of the underlying principles and driving forces that regulate and control the autophagic machinery. Building a representative model of autophagy will require the measurement of the pool sizes of autophagic vesicles, fluxes, and rate constants under basal and perturbed conditions for both macroautophagy and chaperone-mediated autophagy. This will ensure that the model conforms to experimentally derived data points.

SUMMARY, CONCLUSION, AND FUTURE OUTLOOK A deviation in autophagic activity leads to a change in cell death susceptibility (Loos et al., 2013). Key characteristics of the approach of a system are not only the ability to identify and characterize the key parts of a, here autophagy, system and their interaction with one another and their environment but also the power of elucidating the maintenance or failure of the entire system (Kohl and Noble, 2009). In higher-level biological processes such as autophagy, it becomes clear that the system involves multiple levels with numerous feedback control mechanisms but no privileged level of causality (Fig. 2.3A). The major cross-talk between metabolites and the autophagy machinery, including histone-acetylation and epigenetic effects as well as shared metabolic and autophagic checkpoints (Green et al., 2014), strongly suggests a multidirectional transmission of information within the autophagy system. Failure of autophagy systems is associated fundamentally with pathology (Mizushima et al., 2008); however, although the human autophagy system with its protein interaction network has recently been mapped (Behrends et al., 2010), the relationship between its failure or


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dysfunction and autophagic flux deviation as well as cell death onset remains unclear. What could be a way forward to better understand the autophagic system in the context of proteostasis and cell viability? The first step may involve the ability to precisely quantify autophagic and cargo fluxes (Figs. 2.1 and 2.2) and to map the associated parameters (Fig. 2.3A) with their respective changes upon perturbation. This should preferably entail a dynamic analysis during the progression of the disease or upon a given intervention that is known to enhance autophagy, thereby delaying the onset of proteotoxicity (Fig. 2.3B). Correlation analyses would here allow the characterization of the relationship between the autophagy system and cellular proteostasis function in a powerful manner (Tsvetkov et al., 2013). Finally, although we know that deviation in proteostasis may predict cellular degeneration (Tsvetkov et al., 2013), much remains to be done to favorably exploit autophagy modulation. Future work may have to better bring together the here discussed aspects of autophagic flux and the autophagy system, at first in longitudinal and single cell analyses (Mitra et al., 2009), in the context of cell death onset and survival analysis (Jager et al., 2008). This may in the near future, and timely to the 50th birthday of programmed cell death (Lockshin, 2016) allow us not only to predict the risk of cell death when autophagic flux deviates and the autophagy system fails but also to align autophagy modulators therapeutically (Rubinsztein et al., 2012) in favor of cell viability.

Acknowledgments The authors wish to acknowledge financial support from the South African National Research Foundation (NRF), the Medical Research Council, as well as the Cancer Association of South Africa (CANSA).

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C H A P T E R

3 Loss of Pigment Epithelial Cells Is Prevented by Autophagy Yoon H. Kwon, Yeon A. Kim and Young H. Yoo O U T L I N E Age-Related Macular Degeneration

Introduction 106 Anatomy and Histology 106 General Morphology 106 Morphological Polarity 106 Regional Heterogeneity 107 Functional Polarity and Heterogeneity 107 Cellular Junctions 108 Cytoskeletons 108 Function of the RPE 108 Bruch Membrane and IPM Synthesis 108 Absorption of Light 108 Role in Visual Cycle 109 Phagocytosis of Photoreceptor OS and Photoreceptor Renewal 109 Transepithelial Transport of Molecules and Ions, Water 109 Secretion 109 Function in Immune Privilege 110 Exposure to Potential Damage Exposure to Potential Damage Protection From the Light and Oxidative Stress


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Autophagy in the RPEs 111 Overview on Autophagy 111 Autophagy in Retinal Homeostasis 112 Autophagy in RPECs Homeostasis 112 Aging and Autophagy in RPECs 112 Autophagy of Iron-Binding Proteins in RPECs 113 Retinal Pathologic Conditions and Autophagy of RPECs 113 Autophagy of RPECs in Experimental Systems 113 Involvement of Autophagy in RPECs Demise 114 αB-Crystallin and Autophagy αB-Crystallin and Autophagy in RPECs

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Conclusions 115 Acknowledgment 115 References 115

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Abstract

The retinal pigment epithelial cells (RPECs) undertake essential functions for normal outer retinal physiology. RPECs are associated with various retinal pathologic conditions. Owing to its anatomical location in one of the most redox-active interfaces in the human body and the responsibility for routine phagocytosis of photoreceptor outer segments, RPECs are continuously subjected to endogenous and exogenous oxidative injury. Oxidative injury to RPECs causes loss of RPECs, leading to retinal degeneration. It is noticeable that age-related retinal degeneration usually occurs surprisingly late in life irrespective of the constant exposure of RPECs to oxidative stress. This is probably because of that RPECs are more resistant to oxidative stress. Autophagy is involved in cellular homeostasis of retinal pigment epithelium and may be important to ensure the functional integrity of the retina. Furthermore, autophagy seems to regulate functional pathways associated with ocular pathological conditions, including aged macular degeneration which is associated with the loss of RPECs.

INTRODUCTION The retinal pigment epithelium (RPE) consists of retinal pigment epithelial cells (RPECs). RPECs have following essential functions for normal outer retinal physiology: participation in the visual cycle; phagocytosis of outer segments (OSs) of shed photoreceptor; maintenance of the outer blood–retinal barrier; secretion of neurotrophic, inflammatory, and vasculotrophic growth factors; water transport out of the subretinal space; regulation of bidirectional ion and metabolic transport between the retina and the choroid. RPECs are associated with various retinal pathologic conditions.

ANATOMY AND HISTOLOGY General Morphology The RPE extends from the optic nerve to the ora serrata, where it continues as the pigment epithelium of the ciliary body. There are approximately 3.5× 106 RPECs in the adult human eye, and this population remains relatively stable during young adult life in the absence of diseases in which RPE are induced to undergo proliferation or cell death. The foveal area has the highest RPECs density, and the cell density gradually decreases to the peripheral retina.

Morphological Polarity RPECs have highly polarized structure. The 8- to 12-μm-sized nucleus is located in the basal part of the cell. The polarity of RPECs is characterized by distinct structure and specialized functions in the apical and basolateral domains. The apical cell membrane elaborates numerous microvilli (3–7 µm in length) that interdigitate and ensheath the OS of the retinal photoreceptors. RPECs engulf and degrade shed rod OS each day. Each RPEC contacts with several dozens of photoreceptor cells. Thus, each RPEC ingests and degrades hundreds of millions of discs during its lifetime. In addition to this interdigitation, the extracellular matrix (ECM) and neural cell adhesion molecule (N-CAM) expressed on the RPE


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apical surface allow some degree of adhesion between the retina and the RPE. The basal side of RPECs is attached firmly to the underlying Bruch’s membrane. The intracellular distribution of cell organelles in RPE also exhibits polarization. Melanin granules which impart the brown color to RPE and absorbs excess light reaching the photoreceptors are localized at the apical region of the cell, as is the endoplasmic reticulum. With age, RPE gradually lose melanin granules, possibly related to effects of photooxidation. Mitochondria mostly locate in the basal half of the RPE, which results from the oxygen pressure which is highest in this cell region (Gouras et al., 2010). Other cytoplasmic elements, such as microperoxisomes, lysosomes, and phagosomes, do not appear to have a distinct subcellular distribution.

Regional Heterogeneity RPECs exhibit regional heterogeneity. Although the cuboidal RPE appear polygonal in shape when viewed en face cell morphology varies throughout the fundus. RPECs are tall and narrow in the macular area, while they are flatter in the periphery, more spread out, and may be binucleated. The intracellular distribution of melanin pigments in RPECs also exhibits regional heterogeneity. In a healthy retina RPECs of peripheral retina including ora serrata have highest concentration of pigment throughout the cell, while melanin granules are more apical, less frequent, and often elongated at RPECs of the equator and macula. The potential subretinal space that separates the retina and the RPE also show regional heterogeneity. Although the retina firmly attaches to RPE at the optic disc and ora serrata, attachments elsewhere are weak and can be disrupted by relatively weak forces. Due to this characteristic, the retina could be detached by several reasons such as trauma, retinal breaks, and inflammations.

Functional Polarity and Heterogeneity In RPE, some proteins such as Na/K-ATPase pump, ECM metalloproteinase inducer (EMMPRIN), and N-CAM are found at the apical surface, rather than at the basolateral surface where they are found in other epithelia. RPE also predominantly secrete the neurotrophic pigment epithelial-derived factor (PEDF) from the apical side into the interphotoreceptor matrix (IPM), which is about 1000-fold greater than that for vascular endothelial growth factor (VEGF), which is mainly from the basolateral side. A proteomic study showed that apical microvilla have many proteins divided into different functional categories, including retinoid-metabolizing, cytoskeletal, enzymes, ECM components, membrane proteins, and transporters (Bonilha et al., 2004). The basal cell membrane expresses various integrins and shows focal adhesion points with the ECM. Perhaps due to regional differences in requirements for RPE function, RPE cells vary regionally in growth potential, level of expression of vimentin and phosphotyrosine, distribution of Na/K adenosine triphosphatase (ATPase) pumps, and kinetics of rod outer-segment binding and ingestion. Furthermore, age-related alterations in the expression of lysosomal enzymes, Mn-superoxide dismutase, and accumulation of lipofuscin are regionally heterogeneous (Hjelmeland et al., 2010). These findings suggest that this heterogeneity is probably involved in pathological changes in RPECs.


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Cellular Junctions The apical domain of RPECs is sealed by cellular junctions to form the external retinal barrier through joining neighboring cells together and regulating transepithelial diffusion through the paracellular spaces. The RPE have two types of cellular junction: the lateral domains of adjacent RPECs connected by apical zonulae occludens (tight junctions) and adjacent zonulae adherentes (adherens junctions). Nitric oxide is involved in the maintenance of blood–retinal barrier integrity. In pathological conditions, oxidative stress could decrease tight junction protein expression, resulting in the disruption of the integrity of the outer blood–retinal barrier (Bailey et al., 2004). Gap junctions located in the lateral cell membranes are important for the exchange of ions and metabolites between cells.

Cytoskeletons Cytoskeleton in RPECs is highly associated with its distinct functions such as melanosome transport and phagocytosis. The cytoskeleton is composed of three major elements: the actin microfilaments (diameter 7 nm), microtubules (diameter 25 nm), and intermediate filaments (diameter 10 nm). In human RPECs, intermediate filaments of type I (acidic keratins), type II (basic/neutral keratins), and type V (lamins) have been identified.

FUNCTION OF THE RPE Bruch Membrane and IPM Synthesis RPECs synthesize Bruch membrane and the IPM. Bruch’s membrane is a thin (2–4 µm), acellular, ECM located between the retina and choroid. Bruch’s membrane, from the RPE to the choroid, consists of following distinct five layers: the basement membrane of the RPE, the inner collagenous layer, the elastic layer, the outer collagenous layer, and the choriocapillaris endothelium basement membrane. In addition to serving as the attachment site for the RPECs, Bruch serves as a selective conduit for nutrients transported to the retina from the choroidal vasculature and for metabolic wastes transported from the retina to the circulation. Both the RPE and choroid are able to synthesize the major components of Bruch’s membrane. It seems appears that the basal lamina of RPE would be maintained by RPECs, whereas the inner, outer collagenous layer and the elastic layer would be maintained cooperatively by both tissues. RPECs with the inner segments of the photoreceptors synthesize also the IPM in which the apical domain of RPECs is embedded. The IPM is involved in retinoid transport between the photoreceptors and the RPE. Major protein components of IPM include the interphotoreceptor-binding protein, retinol-binding protein (RBP), and transthyretin (TTR) (Adler and Evans, 1985).

Absorption of Light RPECs absorb light that passes beyond the OS of the photoreceptors. Melanin pigment in RPECs absorbs stray photons of light that minimizes light scatter within the retina and protects from excess light. I. MOLECULAR MECHANISMS

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Role in Visual Cycle There are two types of light-sensitive pigments that are part of the membranes of photoreceptor OS, rhodopsin, and opsin. RPECs in cooperation with the photoreceptors recycle these pigments through a complex series of oxidation–reduction reactions and transport mechanisms. A reisomerization of all-trans to 11-cis-retinal occurs in RPE cells.

Phagocytosis of Photoreceptor OS and Photoreceptor Renewal Light energy onto retina and reactive oxygen species by photooxidation leads to destruction of OS of the photoreceptor. The destroyed materials are ingested and degraded by RPECs. This phagocytosis is a highly specialized receptor-mediated, multistep process that comprises recognition, attachment, internalization rate, and degradation of the ingested OS (Kevany and Palczewski, 2010). With age and pathologic changes, degradation of OS materials within the phagolysosomes leads to the formation of lipofuscin granules composed of rod OS residue (Cai et al., 2000).

Transepithelial Transport of Molecules and Ions, Water RPECs play an important role in the transport of nutrients from the circulation to the retina and water and metabolic waste products from the retina to the circulation. Due to blood– retinal barrier, water and ions or other molecules must be actively transported transcellularly. Glucose is one of the most important nutrients that RPECs deliver; RPECs express very high levels of the glucose transporters, GLUT1 and GLUT3. GLUT1 transports glucose and mediates the uptake of vitamin C, which is important to removal of harmful free radicals in RPECs. GLUT3 is responsible for the basal transport of glucose to maintain resting-level activity and have high glucose affinity. Vitamin A, which is an important substance for vision, is transported from the blood to the RPE bound to a complex of RBP and TTR. Ions are transported in and out of RPECs via selective channels. Water is eliminated from the subretinal space by active transport by the RPE and is mediated by the transepithelial transport of chloride ion from the subretinal space, across the RPE to the choroid (Moseley et al., 1984). Water movement across the RPE is also facilitated by Aquaporin-1 channels (Motulsky et al., 2010).

Secretion RPE cells secrete numerous cytokines and growth factors. Cytokines and growth factors regulate many cellular pathways necessary for RPECs function. Cytokines and growth factors secreted by RPECs are as follows: VEGF, PEDF, nerve growth factor (NGF), brainderived neurotrophic factor (BDNF), neurotrophin-3 (NT-3), insulin-like growth factor (IGF1), neuroprotectin 1 (NPD1), transforming growth factor-β (TGF-β), granulocyte-macrophage colony stimulating factor (GM-CSF), monocyte chemotactic protein-1, hepatocyte growth factor (HGF), erythropoietin (EPO), melanoma growth stimulatory activity/growth-regulated protein (MGSA/GRO), endothelin 1, fibroblast growth factor, bone morphogenetic protein, interleukin-6, interleukin-8, connective tissue growth factor. The above factors regulate many cellular pathways necessary for retinal homeostasis. I. MOLECULAR MECHANISMS

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Function in Immune Privilege Subretinal space is immune privilege space. RPECs play a major role in immune privilege. RPECs have not lymphatic drainage from subretinal space and have low levels of major histocompatibility antigen expression. Moreover, PRECs can modulate the immune system by secreting immune modulatory factors and by expressing membrane receptor surface molecules which coordinate the regulation of the immune system. TGF-β is a major factor in the inhibition of T-cell proliferation and IFN-γ production, and the generation of T-regulatory cells (Tregs) in ocular immune-privileged sites (Masli and Vega, 2011). Tight junctions between RPECs play a role as passive physical barrier.

EXPOSURE TO POTENTIAL DAMAGE Exposure to Potential Damage Owing to its anatomical location in one of the most redox active interfaces in the human body and the responsibility for routine phagocytosis of photoreceptor OSs, RPECs are continuously subjected to endogenous and exogenous oxidative injury. Exogenous oxidants are an important source of environmental stress in RPE injury. Light also leads to lipid peroxidation of the disc membranes in the photoreceptor OS (Zhou et al., 2005). During this process, intracellular H2O2 resulting from NADPH in the phagosome or from β-oxidation of lipids in peroxisomes is largely regenerated (Handa, 2012). Phagocytosis of barely digestible materials results in the accumulation of a complex of highly oxidized and degraded molecules with autofluorescence called lipofuscin in RPECs (Kopitz et al., 2004). Lipofuscin is accumulated with age in RPECs, and the excessive lipofuscin accumulation causes RPECs damage. In addition, cigarette smoke is another major source of environmental oxidative stress for RPECs (Rangasamy et al., 2004). Studies employing animal models strongly suggest the role of oxidative stress in RPE injury. High levels of oxidative stress in superoxide dismutase 1-deficient mice led to the development of Drusen, Bruch’s membrane thickening, and choroidal neovascularization (CNV). Additionally, local superoxide dismutase 2 knockdown induced oxidative damage to proteins, vacuolization, degeneration of the RPE, thickening of Bruch’s membrane, and disorganization or shortening of the inner and OSs of the photoreceptor (Justilien et al., 2007). RPECs dysfunction due to abnormal lipofuscin accumulation is involved in key pathological pathways of retinal diseases (Weng et al., 1999).

Protection From the Light and Oxidative Stress RPECs are exposed to one of the highest oxygen concentrations in the body and to abundant light. The melanin pigment within RPECs absorbs stray photons of light, which minimizes light scatter within the retina and protects from excess light. Light absorbed by the melanin granules increases the temperature of the RPE choroid complex. Although the heat is transported away by the bloodstream, this process induces photooxidative damage. Irrespective of being confronted with such a harmful environment, age-dependent decline in function and viability of RPECs is gradual. This gradual decline indicates that RPECs are


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more resistant to oxidative stress (Kurz et al., 2009). There are numerous reports explaining why RPECs are highly resistant to oxidative stress. RPECs produce a potent neuroprotector neurotrophin 1 that inhibits the expression of proinflammatory genes and enhances the expression of antiapoptotic molecules of the Bcl-2 family, thus promoting survival (Lukiw et al., 2005). Furthermore, RPECs express various antioxidants and their enzymes such as glutathione (GSH), thioredoxins (Trx), and glutaredoxins (Grx), methionine sulfoxide reductases (Msrs), catalase, SOD, and glutathione peroxidase.

Age-Related Macular Degeneration Age-related macular degeneration (AMD) is a representative retinal diseases associated with the loss of RPECs. AMD is a leading cause of central vision loss in the western world. A gradual, age-dependent decline in function and viability of RPE cells, combined with lipofuscin accumulation, leads to AMD. Histologically, there are two types of AMD, i.e., dry type (atrophic) and wet type (neovascular or exudative). More than 80% of patients with AMD belong to the dry type. Approximately 10–20% of individuals with dry AMD tend to progress to the wet type. The initial manifestations of early-stage AMD are drusen and pigmentary changes. At the late stage of dry AMD, geographic atrophy (GA) is frequently found and characterized by extensive loss of RPECs, neighboring photoreceptors, and choriocapillaris. Wet AMD includes CNV and associated manifestations. Pathological changes observed in AMD indicate that oxidative damage is an important factor in disease development. Irrespective of numerous previous experimental studies, how oxidative stress induces RPE injury is not fully understood. Several clinical studies showed that supplementation with antioxidants can slow down disease progression of AMD (Delcourt et al., 1999). Both apoptosis and necrosis were evidenced in RPE cells with oxidative insults under in vivo and in vitro scenarios (Dunaief et al., 2002; Hanus et al., 2013). The initial loss of RPECs in AMD is primarily believed to be a result of apoptosis. RPECs undergoing apoptosis have been readily identified in surgically excised choroidal neovascular membrane from patients with AMD and AMD donor eyes (Dunaief et al., 2002). However, the nature and the underlying mechanism of oxidative stress–driven RPECs death remain controversial to date. It is noticeable that AMD usually occurs surprisingly late in life irrespective of the constant exposure of RPECs to oxidative stress (intense light, high ambient oxygen, and excessive phagocytosis). This is probably because of that RPECs are more resistant to oxidative stress (Kurz et al., 2009).

AUTOPHAGY IN THE RPEs Overview on Autophagy Autophagy is a catabolic process aimed to process aged or damaged organelles, proteins, and cellular debris by engulfing them into a double membrane vesicle called the autophagosome and eliminating them by posterior fusion with the lysosome. Autophagy orchestrates cellular homeostasis and plays a cytoprotective role against various pathogenic insults, including nutrition deprivation, hypoxia, oxidative stress, pathogenic infection, and antitumor drug treatment. Three main forms of autophagy, including microautophagy,


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macroautophagy, and chaperone-mediated autophagy, have been well characterized. Among three forms of autophagy, macroautophagy is the most prevalent form of autophagy. The macroautophagy process can be divided into induction, initiation/nucleation, elongation and closure, i.e., engulfment of cytoplasmic proteins, lipids, and damaged organelles, maturation and fusion with primary lysosomes, and finally, degradation, in which contents are degraded by lysosomal enzymes. Autophagy involves more than 30 autophagy-specific proteins (Atgs), conserved from yeast to mammals. Autophagosome expansion in an early step involves insertion of microtubule-associated protein1A/1B-light chain 3-II (LC3-II) into vacuole membrane. This requires Atg7 (E1-like ubiquitin-activating enzyme), Atg3 (E2-like ubiquitin-conjugation enzymes), Atg5-Atg12-Atg16 complex (E3-like ubiquitin-ligase). Other Atgs work in concert to conjugate phosphatidylethanolamine to LC3-I, thus forming LC3-II. Starvation-induced autophagy is inversely regulated by mammalian target of rapamycin (mTOR), which is activated by phosphoinositide 3-kinase (PI3K), protein kinase B (Akt) induced by insulin or other growth factor (Mizushima and Komatsu, 2011).

Autophagy in Retinal Homeostasis Autophagy is upregulated in a number of neurodegenerative diseases and thus may contribute to cell loss. Autophagy plays a critical role in maintaining retinal homeostasis. Autophagy, together with the proteosomal systems, participates in the removal of damaged proteins and organelles in highly metabolic nondividing cells that exist in a prooxidative retinal environment. Interestingly, autophagy proteins are strongly expressed in the retina. In case of those basal levels of autophagy become dysregulated as either a decrease or an increase in autophagy flux, it will cause significantly detrimental effects on retinal function (Banerjee et al., 2010).

Autophagy in RPECs Homeostasis Autophagy is also involved in cellular homeostasis of RPE. There are two major functions of RPE: phagocytosis of the photoreceptor OSs and visual cycle performance. Each day, RPECs must engulf and digest materials released from the distal parts of OS of photoreceptors by a process called phagocytosis. To collect, degrade, and remove phagocytosed material, the endolysosomal system is crucial (Kim et al., 2013; Oczypok et al., 2013; Strauss, 2005). Recently, activation of macroautophagy was documented to be a primary response of ARPE-19 cells to stress (Giansanti et al., 2013). Another major function of RPE, visual cycle performance, also appears to be linked to a noncanonical form of autophagy that is known as LC3-associated phagocytosis, contributing to the normal supply of vitamin A and therefore to normal vision (Ferguson and Green, 2014; Kim et al., 2013). Moreover, RPECs are postmitotic cells with high metabolic activity. Thus, a high rate of autophagy is expected in RPECs. Balance of phagocytosis and autophagy may be important to ensure the functional integrity of the neural retina.

Aging and Autophagy in RPECs Autophagy is also involved in cellular homeostasis of RPE associated with aging. Physiological lysosomal load may be increased to remove damaged material in RPECs of


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old eye. Impairment of autophagy in aging cells is due to increased intracellular burden of damaged macromolecules and organelles, which is mediated by ROS (McCray and Taylor, 2008). Thus, insufficient digestion of the damaged macromolecules and organelles by old RPECs will lead to progressive accumulation of biological “garbage,” such as lipofuscin (Wang et al., 2009a). Abnormalities in the lysosome-dependent degradation of shed OS of the photoreceptors debris can contribute to the degeneration of RPECs.

Autophagy of Iron-Binding Proteins in RPECs Previous studies suggest that autophagy of iron-binding proteins seems to contribute to the oxidative stress resistance. The lysosomal compartment in RPECs contains only a minute amount of redox-active iron, possibly due to a high content and pronounced autophagy of ironbinding proteins. A high basal expression of iron-binding stress proteins, which during their normal autophagic turnover in lysosomes may temporarily bind iron prior to their degradation, could contribute to the unusual oxidative stress resistance in RPECs (Karlsson et al., 2013).

Retinal Pathologic Conditions and Autophagy of RPECs Autophagy is also involved in the pathogenesis of AMD. A previous study suggested that age-related changes in autophagy may underlie the genetic susceptibility found in patients with AMD and may be associated with the pathogenesis of AMD, and that increased autophagy and exosome-mediated release of intracellular proteins are seen in aged RPE and considered to be involved in drusen formation (Wang et al., 2009a). Moreover, an animal and clinical study showed that autophagosome formation increases in RPE and choroids in aged mice while autophagy regulatory proteins are present in drusen in the retina of old patients with AMD (Wang et al., 2009b). Another study reported that autophagy proteins, autophagosomes, and autophagy were significantly reduced in tissue from human donor AMD eyes and two animal models of AMD (Mitter et al., 2014). Autophagy also has been observed in photoreceptors in animal models of hereditary retinal degeneration (Besirli et al., 2011). Further, adverse effects of autophagy have been described in a mouse model of retinitis pigmentosa and in a rat model of ischemia (Piras et al., 2011; Punzo et al., 2009). Although advances have been made in the understanding of autophagy in RPECs and autophagy may represent an important therapeutic target in AMD although the effect and interpretation is complex due to a variation in the AMD phenotypes, the information concerning the role of autophagy in the RPE associated with ocular pathological conditions is still limited.

Autophagy of RPECs in Experimental Systems A previous study reported that H2O2 induces activation of autophagy in RPECs. Another study using H2O2 showed that acute (3 and 24 h) oxidative stress led to a marked increase in autophagy, whereas chronic (14 days) oxidative stress reduced autophagy (Mitter et al., 2014). A2E, which is a component of lipofuscin and the most major fluorophore identified in aged human eyes, augmented autophagy in RPECs (Sparrow et al., 2012), indicating that autophagy in RPECs is a vital cytoprotective process that prevents the accumulation of damaged cellular molecules (Saadat et al., 2014). Methylglyoxal, which is a major precursor


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of advanced glycation end products and an endogenous metabolite primarily resulting from glucose metabolism, also significantly enhanced autophagy flux and increased intracellular accumulation of autophagosomes through Akt, extracellular signal–regulated kinases 1/2 (ERK1/2), c-Jun N-terminal kinases (JNK), and p38 mitogen-activated protein kinases (p38 MAPK) in RPECs. High glucose also increased autophagy in RPECs (Shi et al., 2015). Proteasome inhibitors also activated autophagy RPECs (Viiri et al., 2013; Viiri et al., 2010). Proteasome inhibitor–induced autophagy evoked the accumulation of perinuclear aggregates that strongly colocalized with nucleoporin 62 (p62), an autophagy receptor connecting proteasomal clearance with lysosomes (Bjorkoy et al., 2005; Korolchuk et al., 2009; Viiri et al., 2013). Induction of autophagy in RPECs by rapamycin showed that autophagy plays in protecting RPECs against oxidative stress (Mitter et al., 2014). A mitochondrial complex I inhibitor rotenone increased the level of autophagy in the RPECs undergoing mitotic catastrophe (Lee et al., 2014). Cigarette smoking was also shown to upregulate p62 in RPECs, indicating that p62-mediated autophagy may become the major route to remove impaired proteins in response to cigarette smoking (Viiri et al., 2013). EtOH treatment also increased cytoprotective autophagy in RPECs (Flores-Bellver et al., 2014).

Involvement of Autophagy in RPECs Demise Although autophagy is usually a physiological mechanism that eliminates toxic wastes or damaged cellular components in response to stress, overactive autophagy can lead to autophagic cell death (Cheng et al., 2009; Levine and Yuan, 2005). In this context, autophagy is a form of type II programmed cell death. Autophagic cell death is morphologically defined as occurring in the absence of chromatin condensation, massive autophagic vacuolization, and little or no uptake by neighboring cells (Kroemer et al., 2009). Autophagic cell death in the retina has been reported to occur in a variety of retinal cells under oxidative stress (Mitter et al., 2012). A study showed that inhibition of autophagy flux induces RPECs death (Yoon et al., 2010). A previous study using in vitro simulation AMD model reported that mitophagy contributes the cytoprotection of RPECs undergoing mitotic catastrophe. In addition, the study showed that RPECs undergoing mitotic catastrophe are vulnerable to autophagy inhibition, indicating that mitophagy/autophagy contributes cytoprotection (Lee et al., 2014). However, the interactions between apoptosis and autophagy, as well as their roles in the injury of RPECs in response to stress, have not been adequately addressed. Furthermore, the mechanism by which autophagy regulates RPECs demise in AMD is still unclear. Neither the role of autophagy in the proliferation of the RPECs in proliferative vitreoretinopathy (PVR) nor its regulation as a therapeutic strategy for PVR has not been documented yet.

αB-CRYSTALLIN AND AUTOPHAGY α-Crystallins are prominent members of the small heat shock protein family. αA- and αB-crystallins have been shown to be present in a number of tissues. Their expression and function in the eye, particularly in the lens, has been extensively studied (Andley, 2007). Apart from the well-recognized chaperone effect, a wide variety of other properties of α-crystallins have come to the force in various tissues including the eye. These include antiinflammatory, antifibrillar, and antiapoptotic properties, protection against ER stress and autophagy, modulation I. MOLECULAR MECHANISMS

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of angiogenesis as well as protein–protein interactions with a large array of proteins (Kannan et al., 2012; Kase et al., 2010). αB-crystallin is expressed in RPECs and is the principal antiapoptotic factor in those cells. We previously demonstrated that αB-crystallin siRNA sensitizes RPE cells to SAHA-induced apoptosis through abolishing the association of αB-crystallin with HDAC1 in SC35 speckles RPECs (Noh et al., 2008). We also showed that αB-crystallin prevents caspase activation by physically interacting with caspase subtypes in the cytoplasm and nucleus, thereby protecting RPECs from methylglyoxal-induced apoptosis RPECs (Jeong et al., 2012). Recently, our previous study using in vitro simulation AMD model reported that B-crystallin prevents RPECs undergoing mitotic catastrophe from plunging into cell death (Lee et al., 2014). The prevention of apoptosis in RPECs by αB-crystallin has significance in two pathologic ocular conditions. Because RPECs may be lost by apoptosis in AMD, αB-crystallin may play a role in preventing the onset of AMD. Conversely, αB-crystallin could inhibit the efficacy of therapeutics in inducing apoptosis in epiretinal membranes in patients with PVR.

αB-Crystallin and Autophagy in RPECs Increase in αB-crystallin expression in neurodegenerative diseases such as AMD has been documented (Crabb et al., 2002; De et al., 2007; Nakata et al., 2005). It was postulated that the presence of αB-crystallin in drusen could be in response to toxic protein aggregation and lipofuscin accumulation. Previous studies reported the presence of autophagic and exosomal markers in drusen from patients with AMD, indicating that increased autophagy and exocytic activities in aged RPE could supply extracellular materials for the formation of drusen (Wang et al., 2009b). Since there is little information concerning the role of αB-crystallin in autophagy in the RPECs, further future study is a challenging task.

CONCLUSIONS The reports on the role of autophagy in RPECs are recently increasing. However, the information on the role of autophagy in RPECs homeostasis is still lacking. Autophagy also seems to regulate functional pathways associated with ocular pathological conditions. However, the information concerning the role of autophagy in RPECs associated with ocular pathological conditions is largely unknown. Further study on the role of autophagy in RPECs and its implication in retinal pathologic conditions is a challenging task.

Acknowledgment This work was supported by the National Research Foundation of Korea grant funded by the Korea government (No. 2014 001483 and 2015R1A2A1A10051603).

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4 Role of Autophagy Inhibition in Regulating Hepatic Lipid Metabolism: Molecular Cross Talk Between Proteasome Activator REGγ and SirT1 Signaling Xiaotao Li and Lei Li O U T L I N E Introduction 120 Proteasome Links Autophage and Lipid Metabolism–Molecular Mechanisms 123 REGγ and Ub-Independent Proteasome Systems 123 REGγ Regulates Hepatic Lipid Metabolism Through Inhibition of Autophagy 124

Molecular Switch: REGγ-Sirt1 Cross Talk Modulates Autophage Activity in Lipid Metabolism 126 SirT1 (Yeast Sir2) as a Nutrient/ Metabolic Sensor 127 REGγ-SirT1 Regulates Lipid Metabolism by Modulating Autophagy 127 Discussion 129 Acknowledgments 130 References 130


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4. ROLE OF AUTOPHAGY INHIBITION IN REGULATING HEPATIC LIPID METABOLISM

Abstract

With an increase in the metabolic disorders, there is a growing need to further understand the mechanisms of lipid metabolism. Recent studies have identified that two major proteolytic degradative pathways— autophagy and proteasome—are mutually regulated and play a critical role in modulating cellular lipid homeostasis. Linking these two pathways is the REGγ-SirT1 complex, and different energy contexts can affect the interactions between these two proteins, which further influences the autophagy activity and lipid metabolism. The recent study highlights the potential of the REGγ-SirT1-autophagy pathway as the alternative and promising therapeutic target for the treatment of metabolic disorders like type 2 diabetes, obesity, and liver steatosis.

INTRODUCTION Recently, with incidences of metabolic disorders, such as type 2 diabetes (T2D), obesity, and liver steatosis, having been skyrocketing worldwide, the need to control the disease has become urgent increased. Recent research has devoted to unveiling previously unknown mechanisms for lipid and lipoprotein metabolism. Pushing and obtaining further knowledge for lipid metabolism may help to locate and identify new drug targets for the treatment of metabolic syndrome. Unexpectedly, several recent exciting discoveries have brought together seemingly unrelated pathways that are essential for regulation of lipid homeostasis (Dong et al., 2013; Singh et al., 2009a). The two major cellular proteolytic degradative systems, autophagy and proteasome, have now been confirmed to play a significant role in lipid metabolism and to maintain lipid homeostasis. The two pathways are functionally coupled: inhibiting autophagy results in the compromised proteasomal activity in the cell, and conversely, blocking proteasome can activate autophagy. In reviewing the latest discoveries on the cross talk between the two pathways for regulation of cellular lipid metabolism, we will gain the molecular details underlying such a regulation. It is also intriguing that such a complex regulatory network is knitted by a master switch, the REGγSirT1 complex, and controls the consequences of lipid metabolism under different nutrient conditions. Recent years have seen a significant advancement in understanding the new role of autophagy in lipid metabolism. Autophagy has been indicated in the regulation of lipid stores in two major organs that are critical for lipid homeostasis: the liver and the adipose tissue. Furthering our understanding of the regulatory role of autophagy in the metabolism of lipids and lipoproteins will open a new avenue to identify new pharmacological targets for treating metabolic complications like T2D, obesity, prediabetes, and the metabolic syndrome; therefore, the information gleaned from latest studies can be very inspiring and instructive. Recent discoveries also identified the molecular cross talk between ubiquitin-independent proteasome signaling pathway and autophagy in the regulation of lipid metabolism, further unveiling the complex regulatory network and highlighting the great opportunities for us to search for new generation of drug targets for metabolic diseases. Autophagy is a highly ordered process to dissemble unwanted or dysfunctional cellular components covering misfolded proteins and excess or damaged organelles. The pathway may be an evolutionarily adaptive strategy to benefit the survival of the cell in the contexts of disease and nutritional restriction: autophagic failure to remove abnormal protein aggregates has been implicated in diseases like Huntington’s or α-1 antitrypsin deficiency; and in


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the extreme case of starvation, cellular components can be degraded and recycled to promote cellular survival by maintaining cellular energy levels. Therefore autophagy poises as a protective mechanism for the cell against physiological stress. Autophagy is categorized into three types: chaperone-mediated autophagy (CMA), microautophagy, and macroautophagy. CMA has a specific substrate requirement where proteins of specific consensus sequences are recognized by the lysosomal hsc70 chaperone for degradation. In microautophagy invagination of a small portion of the lysosomal membrane renders direct engulfment of the cytoplasmic components in the vicinity of the lysosomal surface. In contrast to the aforementioned two types of autophagy, macroautophagy is the major pathway that has been extensively studied (hereafter referred as autophagy for this review). It is a highly ordered process and subjected to tight regulation in the sense that the formation of autophagosome, a double-membraned compartment that isolates its cargos from the rest of the cell, is orchestrated by a class of autophagy-related genes (i.e., the atg genes), and that the maturation and fusion of autophagosomes to the lysosomes, as well as the lysosomal degradation, are tightly organized and regulated. Contrary to the traditional view where autophagy was indicated in maintaining cellular energetic balance during nutritional starvation by recycling amino acids, a surge of interest of its new role has been revived by the discovery that autophagy can also provide free fatty acids (FFAs) to meet the cellular energy needs. Furthermore, given the versatility of autophagy in cellular development and differentiation, cancer and neurodegenerative disorders, aging, and innate and adaptive immunity, and the striking regulatory and functional similarities between autophagy and lipolysis, it is not surprising that autophagy also plays a role in lipid metabolism (Fig. 4.1).

FIGURE 4.1 Autophagy degrades lipids in the liver and regulates hepatic lipid stores. Small lipid droplets in hepatocytes are engulfed by autophagosomes, either alone or along with the organelles like mitochondria. Large lipid droplets are engulfed by a fraction and sequestered in the autophagosomes, which in turn fuse with lysosomes, where the cargos are degraded. The triglycerides in the lipid droplets are degraded to free fatty acids, which are later subject to β-oxidation in mitochondria and produce ATP.


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Fatty acids are toxic in the free form to cells. Coping with this problem, cells store FFAs in the esterified forms within cytoplasmic lipid droplets (LDs). As a result, LDs exist in the cell as a storage organelle for excess lipid esters; and the major forms of these lipids include triglycerides (TGs) and cholesterol esters, which are surrounded by a phospholipid monolayer and specific LD-related proteins (Brasaemle and Wolins, 2012; Martin and Parton, 2006). Conceivably, these cellular LDs is subject to regulation of lysosomal or proteasomal degradation pathways with regard to lipid metabolism in the cell—conversion of FAAs to TGs, storage of TGs, and lipolysis of TGs into FAAs for mitochondrial β-oxidation to provide the cell with ATP—but the underlying mechanisms and site of LD mobilization and lipolysis await to be revealed. The notion that LDs are also subject to autophagic breakdown initially comes from the clue that acid lipases are presented within lysosomes. Following the notion came with a body of experimental evidence supporting the role of autophagy in hepatocyte lipid metabolism (Singh et al., 2009a). Firstly, cellular TGs were significantly increased by genetic knockdown of the autophagy gene atg5 or pharmacological inhibition of 3-methyladenine (3-MA) in hepatocytes treated with oleate or cultured in methionine and choline-deficient medium (i.e., two ways to promote TG formation). Accordingly, the size and number of LDs were elevated. The accumulating lipid storage could be ascribed to failed lipid breakdown, as both lipolysis and rate of β-oxidation had been decreased. In addition, the same autophagy function was also observed in murine embryonic fibroblasts (MEFs), indicating the role of autophagy in lipid metabolism is a general case. Secondly, it was evident that lipid was channeled through the autophagy pathway because LDs and the autophagosomal marker LC3 were colocalized. Electron microscopy also identified LDs within the autophagic vacuoles. Thirdly and significantly, in an in vivo mouse model where hepatocyte-specific atg7 gene was knocked out, oil red O staining in the liver and hepatic TGs and LD-associated proteins TIP47 and ADRP were all elevated upon starvation, suggesting that disrupting autophagy could lead to liver steatosis. The effect of autophagy on lipid storage in adipocytes is opposite to that of in the hepatocytes: while autophagy is required for degradative function in hepatocytes, its activity in adipocytes is to increase the lipid stores. Pharmacological treatment with 3-MA or atg7 knockdown in preadipocytes 3T3-L1 would block differentiation of these cells into mature adipocytes. TG accumulation and LD formation, the phenomena usually accompanied with the differentiation process, were diminished, too (Singh et al., 2009b). The same effects were also observed for MEFs that had had atg5 knocked out when induced to differentiate into adipocytes (Baerga et al., 2009). In an in vivo model of adipocyte-specific atg7 knockout, white adipose tissue (WAT), a major fat storage site in the body, was reduced, with increased level of brown adipose tissue (BAT). Interestingly, the LDs within adipocytes in WAT of the knockout animals were smaller than the controls; and both WAT and BAT had enhanced lipid breakdown, as increased rates of β-oxidation were recorded for both tissues. Therefore a very different role of autophagy in promoting lipid storage has been suggested for adipocytes, and it is in contrast to its role in degradative pathway for hepatocytes. In addition, in vitro evidence has suggested that autophagy positively regulates adipocyte differentiation process. But the regulatory mechanism remains unclear—answers to this question will help to demonstrate the critical role of autophagy in the overall lipid homeostasis of the body and may pave a new way to treat lipid metabolism-related diseases like obesity, which can be exemplified by converting WAT into BAT in human adults (Nedergaard et al., 2007; Virtanen et al., 2009).


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As stated earlier, conversion of WAT into BAT can be a viable strategy to treat obesity. As an example of autophagy being a therapeutic target for metabolic diseases, in vivo results from the atg7-knockout mice have offered the possibility of manipulating adipocyte autophagy: the animals were lean due to predominant BAT over WAT (Czaja, 2010). Therefore autophagy in adipocytes may be a potential target for obesity management (Spiegelman and Flier, 2001; Virtanen et al., 2009). Conceivably, tissue-specific manipulation of autophagy may have very different outcomes. For instance, reducing hepatic autophagy may promote insulin resistance; but adipocytespecific autophagic blockage could sensitize insulin signaling (Amir and Czaja, 2011; Singh et al., 2009b; Yang et al., 2010). Although reciprocal regulation in the feedback loops of autophagy and insulin signaling is complex (Finn and Dice, 2006; Yang et al., 2010), it still holds promising for autophagy as an alternative therapeutic target for metabolic disease.

PROTEASOME LINKS AUTOPHAGE AND LIPID METABOLISM–MOLECULAR MECHANISMS In the cell there are two major proteolytic systems: the proteasome and autophagy. Intriguingly, these two systems functionally interplay in which inhibition of either one will have consequence on the other pathway. It has been shown that blocking autophagy could lead to compromised degradation of ubiquitin-proteasome substrates, while inhibiting proteasome functions would activate autophagy (Ding et al., 2007b; Korolchuk et al., 2009). The proteasome exists as a large protein complex and comprises a 20S proteolytic core and three proteasomal activators, namely, 19S (or PA700), 11S (or PA28, REG), and PA200. Binding to the 20S core, the 19S activator mainly mediates degradation of ubiquitinated proteins, while the 11S activator facilitates Ub-independent degradative pathway. In contrast to the Ub-dependent proteasomal pathway, less attention has been drawn to the Ub-independent degradation. Center to Ub-independent pathway is REGγ (PA28γ), one of the 11S proteasomal activators (Dubiel et al., 1992; Ma et al., 1992). Previous studies have suggested that REGγ promotes Ub- and ATP-independent proteolytic turnover of SRC-3/AIB1 (steroid receptor coactivator-3) and p21, highlighting its regulation in cell cycle regulation (Li et al., 2006, 2007). Strikingly, a recent study has identified a previously unknown function of Ub-independent REGγ-proteasome in regulating autophagy and lipid homeostasis (Dong et al., 2013). Specifically, REGγ modulates SirT1 (Sirtuin 1, homolog of yeast Sir2) activity under normal or restrictive energy conditions and acts as a master regulator of hepatic lipid metabolism by switching off/on autophagy in the liver. Therefore REGγ may represent as a potential therapeutic target for metabolic disorders. In the following sections, we will discuss the molecular detail of REGγ regulating various biological functions as well as its role in hepatic lipid metabolism.

REGγ and Ub-Independent Proteasome Systems The proteasome activators, known as 11S REG or PA28 that is comprised of three homologs α, β, and γ, were discovered two decades ago (Dubiel et al., 1992; Ma et al., 1992). They are homo- (γ) or heteroheptameric (α and β) rings that bind to the ends of 20S proteasomal cores and activate protein degradative pathway in an Ub-independent manner. REGα and


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FIGURE 4.2 REGγ-proteasome plays versatile roles in the regulation of cell cycle, apoptosis, DNA damage response, and tumorigenesis. The tumor suppressor protein p53 is subject to REGγ-proteasomal degradation. Deficient REGγ leads to increased p53 protein levels in several cancer cell lines by eliminating degradation of p53 by MDM2. Depletion of REGγ also hinders the cellular response to drug resistance, proliferation, cell cycle progression, and proteasomal activity via p53/TGF-β signaling. REGγ can also bind to and facilitate the degradation of p21 and SRC-3 by the 20S proteasome in an ATP- and ubiquitin-independent manner. Aberrant degradation of these proteins is linked to inappropriate cell cycle progression, apoptosis, and abnormal cellular proliferation, which has a pathological implication in cancer development.

β subunits are expressed in many organs and particularly abundant in immune tissues but are virtually absent from the brain. By contrast, large amounts of REGγ are expressed in the brain, with moderate levels in other organs (Li and Rechsteiner, 2001; Yu et al., 2010). Distinct from the biological functions of REGαβ, which have indications in cellular immunity, the functional implications of REGγ in the cell appear to be multidimensional (Fig. 4.2) (Mao et al., 2008). We will first review the implications of REGγ in apoptosis, cell cycle regulation, and cancers. We will then discuss the latest discovery that it also regulates lipid homeostasis via autophagy.

REGγ Regulates Hepatic Lipid Metabolism Through Inhibition of Autophagy The first hint that REGγ may be involved in metabolism derived from the previous observation that REGγ-KO mice exhibited growth retardation and reduced body weight (Barton


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et al., 2004; Murata et al., 1999). Further investigation supported the notion that REGγ-KO mice were protected from high-fat diet (HFD)-induced hepatic steatosis. The REGγ-KO mice did not develop liver steatosis even after 19-week HFD feeding, and oil red O staining of the livers from the knockout mice was significantly reduced compared with that of the wild-type livers. Furthermore, the liver and serum TG levels have been markedly elevated in wild-type mice challenged with HFD. Importantly, in vitro overexpression of REGγ in human hepatocellular carcinoma (HepG2) cells resulted in lipid accumulation and increased LD size, offering another layer of evidence that REGγ had played a direct role in regulating hepatic lipid metabolism. This function is specific to REGγ because expression of REGα or REGβ did not have such an effect. Both in vivo and in vitro evidence suggests that the regulation of REGγ on lipid metabolism is through inhibition of autophagy. Electron microscopic examination showed that REGγ knockout mice had significantly increased number of autophagic vacuoles, regardless they were fed on HFD or normal diet. Moreover, the number and the size of LDs in the knockout animals fed on HFD were significantly reduced compared with that of wild-type mice on HFD. Importantly, change of two autophagic markers (i.e., increasing level of LC3-II and decreasing level of p62) in REGγ-knockout livers was consistent with a higher autophagy level in the knockout animals. Similar results were obtained in REGγ-knocked down cells of MEF, HeLa, and H1299, too. Therefore, increased autophagy was accounted for protection of HFD-induced hepatic steatosis in the REGγ knockout mice. The identification of REGγ in the regulation of lipid metabolism has linked blocked proteasomal function and activation of autophagy. As a result, this proteasome activator is critical for maintaining the balance between the proteasome system and autophagy as far as modulating lipid metabolism is concerned. Therefore, because REGγ specifically activates Ub-independent proteasomal pathway, it is conceivable that cells may use autophagy as an alternative to degrade LDs when the Ub-independent pathways is hindered. On the other hand, although suppression of proteasome may induce ER stress, which in turn will activate autophagy and contribute to metabolic syndrome and liver steatosis (Ding et al., 2007a; Fu et al., 2011, 2012), the effect of REGγ-knockout induced autophagy was not likely due to ER stress (Dong et al., 2013). It is worth noting that in another study, when knocking out all three members of REG activators, namely, REGα, REGβ, and REGγ, the triple-REG-knockout mice showed decreased hepatic sensitivity to insulin, which led to minor hepatic steatosis under normal diet (Otoda et al., 2013). In contrast, the REGγ-knockout animals showed resistance to liver steatosis. The discrepancy is not difficult to reconcile, though, because triple-REGknockout mice may have triggered an unfolded protein response and ER stress in the liver, while REGγ-knockout did not affect the ER homeostasis, and therefore, removal of all three members may be too complicated to attribute the right phenotype for each member of REG activator. In addition, considering the enhanced autophagic phenotype of REGγ-knockout could not be rescued by overexpression of the other two members, REGα/β, the two groups of REG activators may have very different biological functions (Dubiel et al., 1992; Ma et al., 1992). Therefore the role of REGγ regulating hepatic lipid metabolism has been convincingly established (Dong et al., 2013).


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MOLECULAR SWITCH: REGγ-SIRT1 CROSS TALK MODULATES AUTOPHAGE ACTIVITY IN LIPID METABOLISM The previous unknown function of REGγ-proteasome in regulating lipid metabolism through inhibition of autophagy is intriguing. What is left to be determined is how the regulation is achieved molecularly. The recent study has identified SirT1 as the key factor linking Ub-independent proteasome and autophagy in regulating hepatic lipid metabolism (Fig. 4.3). The REGγ-SirT1 complex functions as a molecular switch in response to different energy conditions: under normal conditions, REGγ directly withholds SirT1 and directs it to Ub-independent proteasomal degradation, inhibiting its activity of binding and deacetylating autophagy proteins (i.e., Atg5 and Atg7), thus maintaining autophagy at a low basal level; during energy deprivation, however, activated SirT1 phosphorylation by AMPK (AMP-activated protein kinase) liberates it from the REGγ-SirT1 complex and promotes SirT1 interacting with the Atg proteins, which results in enhanced autophagy activity in degrading cellular lipids. Therefore, REGγ-SirT1 together regulates hepatic lipid

FIGURE 4.3 The REGγ-SirT1 complex functions as a molecular switch to regulate hepatic lipid homeostasis. Under normal conditions, REGγ sequesters SirT1 and directs it to proteasomal degradation. As a result, SirT1 cannot bind and deacetylate Atg5/7, which keeps cellular autophagy at a basal level. Under energy-deprivation conditions, however, SirT1 is dissociated from REGγ and activated by phosphorylation of AMPK, the cellular energy sensor. The activated SirT1 binds to and deacetylates the autophagic proteins Atg5/7, which leads to elevated autophagy activity. AMPK, AMP-activated protein kinase.


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homeostasis in a SirT1- and autophagy-dependent manner. In the following sections, we will discuss the details of REGγ-SirT1 signaling modulating autophagy activity in hepatic lipid metabolism.

SirT1 (Yeast Sir2) as a Nutrient/Metabolic Sensor In the work of Dong et al., SirT1 was identified as an interactor of REGγ in a large-scale proteomic screen in REGγ-positive and REGγ-null MEF cells (Dong et al., 2013). SirT1 is an NAD+-dependent type III deacetylase that deacetylates proteins that function in response to stress, nutrition, and metabolic changes in the cell. Its function in modulating glucose homeostasis, insulin sensitivity, and longevity has been well documented (Nemoto et al., 2005; Rodgers et al., 2005; Sun et al., 2007). In liver, fasting signals are transduced by pyruvate and induce SirT1 protein. Activated SirT1 interacts with and deacetylates PGC-1α (peroxisome proliferator-activated receptor-gamma coactivator 1α) at specific lysine residues in an NAD+-dependent manner. Therefore SirT1 regulates the gluconeogenic/glycolytic pathways in liver through modulation of PGC-1α function (Nemoto et al., 2005; Rodgers et al., 2005). SirT1 also regulates gluconeogenesis by an additional pathway through CRTC2 (CREB-regulated transcription coactivator 2) (Liu et al., 2008). Another aspect of SirT1 function in maintaining energy balance lies in the fact that SirT1 can promote insulin sensitivity under insulin-resistant conditions by repressing PTP1B transcription (Sun et al., 2007). Backing this notion, resveratrol, a SirT1 activator, can boost insulin sensitivity both in vitro and in vivo, further confirming the critical role of SirT1 in energy metabolism (Lagouge et al., 2006; Sun et al., 2007). Collectively, a picture of convergent biological effects of AMPKSirT1 pathway on energy metabolism has emerged: AMPK, the master intracellular metabolic sensor of AMP/ATP ratio in eukaryotes, can activate deacetylation of an array of SirT1 substrates including PGC-1α, CRTC2, FOXO1 (forkhead box O1), and FOXO3a (Canto et al., 2009; Nemoto et al., 2004).

REGγ-SirT1 Regulates Lipid Metabolism by Modulating Autophagy Previously, several studies have reported that SirT1 can regulate autophagy by deacetylating multiple autophagy proteins (i.e., Atg5, Atg7, and Atg8) in an NAD-dependent manner (Lee et al., 2008). Interestingly, Sirt1−/− mice resemble Atg5 knockout animals in that they are born normally but die within hours to days after birth. Examination of organelle morphology for Sirt1−/− mice is consistent with the phenotype of the atg-deficient animals (Komatsu et al., 2005), too. Despite these exciting results, however, the molecular factors and mechanisms that control SirT1 autophagic function had remained unknown until the recent discovery offered a new perspective in terms of REGγ-proteasome modulating the activity of SirT1 to deacetylate the autophagic proteins. SirT1 has been indicated to regulate lipid metabolism in the body: some reports have suggested that SirT1 can reduce fat accumulation in white adipose through modulating the fat regulator PPARγ (peroxisome proliferator-activated receptor γ) (Picard et al., 2004). In differentiated fat cells, upregulation of Sirt1 triggers lipolysis and loss of fat. Interestingly, by the same token, by acetylating PPARγ, SirT1 can also promote browning of white adipose


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(Qiang et al., 2012). More importantly, the specific regulation of liver steatosis has been linked to the function of SirT1. Pfluger et al. have reported that transgenic Sirt1 mice under an HFD showed lower lipid-induced inflammation along with better glucose tolerance and were protected from HFD-induced hepatic steatosis (Pfluger et al., 2008). On the contrary, liver-specific Sirt1 knockout mice under HFD develop hepatic steatosis, hepatic inflammation, and ER stress, suggesting that SirT1 plays a vital role in the regulation of hepatic lipid homeostasis (Purushotham et al., 2009). We have now known, unexpectedly, that REGγ can fine-tune the activity of SirT1 in maintaining the cellular lipid homeostasis. As such, in light of the role of SirT1 in autophagy regulation and that of autophagy in lipid metabolism, the recent study has provided the molecular details of SirT1 affecting hepatic lipid metabolism by modulating autophagy functions (Dong et al., 2013). A convergent biological role of proteasome system, deacetylase, and autophagy has emerged to account for an alternative pathway for lipid metabolism in the liver. Linking the regulation of REGγ-proteasome on autophagy, the direct interaction of SirT1 with REGγ has been confirmed, and the interacting regions on REGγ (aa 66–103) and SirT1 (aa 378–458, located in the catalytic domain) have been mapped. Following the discovery, the researchers further confirmed that the function of REGγ on autophagy was SirT1-dependent, because knocking down SirT1 could not rescue the autophagy phenotype induced by REGγ-knockdown. Furthermore, REGγ guides SirT1 to Ub-independent degradation since elevated level of SirT1 has been recorded in the REGγ-deficient cells, and the modulation happened at the posttranslational level. Using a temperature-sensitive cell line harboring a thermolabile ubiquitin-activating enzyme (Li et al., 2007), the researchers validated that REGγ had directed SirT1 to Ub-independent degradative pathway. Therefore the above evidence suggests that SirT1 is subject to direct regulation by REGγ. But what is the molecular detail of REGγ regulating autophagy via SirT1? A more comprehensive picture has emerged: the regulation of REGγ on autophagy is dependent on deacetylation of autophagic machinery proteins (i.e., Atg5 and Atg 7) by SirT1. Consistent with this notion, the acetylation levels of Atg5/Atg7 were reduced in REGγ-knockout animals, and accordingly, pharmacological inhibition of SirT1 activity could not produce REGγ deficiency–induced Atg5/Atg7 deacetylation. Interestingly, overexpression of REGγ selectively inhibits SirT1 activity to deacetylate Atg5/Atg7, but not other SirT1 substrates like p53, suggesting that the effect of REGγ on autophagy is specifically confined to the SirT1 pathway. Taken together, REGγ can directly bind to SirT1 and promote its degradation via Ub-independent pathway. The association of SirT1 with REGγ contributes to displacement of autophagic proteins Atg5/Atg7 from the SirT1-Atg complexes and further impedes deacetylation of the Atg proteins. The consequence of the formation of REGγ-SirT1 complex in the cell is to maintain autophagy at the basal level under normal physiological conditions. With revelation of the role of REGγ in maintaining cellular autophagy under normal conditions, one would naturally interrogate how the regulation is fine-tuned when the energy/ nutrient conditions are altered (Kroemer et al., 2010). Indeed, nutritional stress like glucose deprivation could significantly reduce REGγ-SirT1 binding, and SirT1 is consequently released to deacetylate Atg proteins, which leads to activated autophagy in the cell. Not surprisingly, AMPK, the molecular sensor for cellular energy level, sparks the cellular response to glucose deprivation by phosphorylating SirT1 at T530 and promotes dissociation of SirT1 from REGγ, initiating the whole signaling cascades to activated autophagy (Fig. 4.3).


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Taken what have been known so far, it is evident that the REGγ-SirT1-autophagy cross talk pathway contributes to lipid metabolism and homeostasis in the liver: depending on the energy conditions, the interaction between REGγ-SirT1 is subject to a dynamic regulation. In the context of certain cellular energy level, SirT1 is either sequestered in the REGγSirT1 complex to maintain the basal autophagic activity or freed to interact and activate Atg proteins to promote autophagy-mediated lipid metabolism. As a result, REGγ-SirT1 acts as a master molecular switch in the liver for autophagy-mediated lipid homeostasis.

DISCUSSION The cross talk between the proteasome activator REGγ and SirT1 signaling in the regulation of hepatic lipid metabolism and homeostasis is significant in which it links the two proteolytic pathways—autophagy and proteasome—for the regulation of cellular energy level under different nutrient conditions. Furthermore, toggling the cellular energy balance has a significant impact on the pathogenesis of hepatic steatosis and obesity: although it is likely that additional mechanisms may exist to contribute to maintaining lipid homeostasis, the key components in the coupling of REGγ-proteasome and autophagy pathways can serve as potential pharmacological targets for the treatment of metabolic disorders. This notion is supported by the observation that the autophagy inhibitor chloroquine (CLQ) can nullify the protective roles of REGγ deficiency in HFD-induced liver steatosis in vivo (Dong et al., 2013). Hence, alternative and new therapeutic targets for disordered lipid metabolism may lie outside of what we have previously conceived for the “canonical” lipid metabolism pathways. The discovery also underscores the urgent need to reveal alternative mechanisms that account for metabolism disorders including the prevailing symptoms like T2D and obesity. Previous reports have documented that a mutual regulation between REGγ and SirT1 exists in the cell: REGγ is subject to acetylation by CBP (CREB-binding protein) and deacetylation by SirT1. Acetylation of REGγ is important for its heptamerization and activity; and abrogation of its acetylation will lead to significantly decreased capability to degrade its target substrates, such as p21 and hepatitis C virus core protein (Liu et al., 2013). The mutual regulation has an important implication in autophagy-mediated lipid metabolism, and further investigation should address how such mutual regulation would affect the liver lipid homeostasis. On the other hand, given the fact that starvation markedly reduce the interaction between REGγ and SirT1, it is worth delving into the details of how various energy/nutrient conditions contributing to the regulatory balance between proteasomal activity and autophagy, and importantly, the implications of the REGγ-SirT1 complex in maintaining the cellular lipid homeostasis in the context of mutual regulation between the two proteins. Conceivably, current evidence suggests a possibility that liberation of SirT1 from REGγ may promote starvation-induced increase of proteasome activity through a posttranslational modification mechanism. In addition to its role in cellular metabolism, SirT1 also protects the cell from stress and offers a survival advantage. For example, SirT1 negatively regulates p53-mediated apoptosis in response to DNA damage, offering a growth benefit to the cell. SirT1 also enhances the ability of FOXO3 to induce cell cycle arrest and resistance to oxidative stress (Brunet et al., 2004). Furthermore, a mutual regulation between E2F1 (a cell cycle and apoptosis regulator) and SirT1 can regulate cellular sensitivity to DNA damage (Wang et al., 2006).


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It is thus tempting to speculate that modulation of cellular energy level can be coupled to pathways controlling cellular response to survival stress. In the future studies, it would be worth determining if REGγ-proteasome could modulate the cellular response to stress, and consequently affect the cellular lipid homeostasis. On the other hand, it has been known that SirT1 modulates lipid homeostasis through direct regulations on PPARγ and PGC-1α (Purushotham et al., 2009). Therefore, it would be interesting to know, under different energy conditions, if and how REGγ would affect cellular energy metabolism through the downstream effectors of SirT1. Given the opposite effects of autophagy on lipid storage in adipocytes versus hepatocytes—we have known that autophagy is required for LD degradation in hepatocytes, yet its activity in adipocytes is to increase the lipid stores—another important question now awaits answers: How does REGγ pose an additional layer of regulation on lipid metabolism in these two different tissues? Considering the role of REGγ-SirT1 in hepatic lipid metabolism, future studies should focus on the cross talk of REGγ-proteasome and autophagy, with emphasis on the regulation of SirT1 functions, to answer this question. Particularly, it would be interesting to determine if REGγ interacts with SirT1 in differentiated adipocytes, and more importantly, to evaluate the metabolic consequences of blocking REGγ functions under normal and energy-deprivation conditions. It would also be necessary to measure the rates of lipid degradation and β-oxidation in both WAT and BAT in REGγ-deficient animal models, to define the in vivo biological functions of REGγ in differentiated adipocytes. Since autophagy positively regulates adipocyte differentiation process, another related question is to determine if REGγ can also regulate the differentiation of adipocytes under different energy conditions. Answers to this question and the aforementioned one would provide a more complete picture in terms of REGγ modulating lipid homeostasis in the body. With incidences of metabolic disorders creeping up worldwide, in light of the critical role of REGγ in protecting HFD-induced liver steatosis, one would image that downregulation of REGγ would sensitize the insulin signaling and provide a new strategy for treating diabetes. This view, in combination with the previous finding that autophagy serves as an alternative pathway for degrading excess cellular lipids, will provide new exciting opportunities to identify promising therapeutic targets for maintaining the lipid homeostasis and fixing metabolic abnormalities for the human.

Acknowledgments We appreciate contributions by Dr. Chuangui Wang in the study of REGγ-SirT1 pathway. This manuscript was funded by the National Basic Research Program (2011CB504200, 2015CB910403). This work was also supported in part by grants from National Natural Science Foundation of China (81401837,81471066, 81261120555, 31200878, 31071875, 81271742, 81272943), the Science and Technology Commission of Shanghai Municipality (14430712100), and Shanghai natural science foundation (12ZR1409300).

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5 Role of Autophagy in Regulating Cyclin A2 Degradation: Live-Cell Imaging Abdelhalim Loukil and Marion Peter O U T L I N E Introduction 133 Autophagy Regulates Protein Turnover 134 Mitotic Autophagy, a Failsafe Mechanism 135

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Discussion 139 References 139

Abstract

Cyclin A2 is an essential regulator of the cell cycle. Its degradation by the ubiquitin-proteasome system (UPS) has been characterized for years. When studying cyclin A2 degradation, using notably high-resolution live-cell imaging, we recently showed that autophagy is an additional pathway for cyclin A2 degradation. After presenting data from the literature related to autophagy in general, and in particular during mitosis, we comment on our data regarding cyclin A2 degradation by autophagy and emphasize the interest of livecell imaging in this context.

INTRODUCTION The cell division cycle is orchestrated by cyclin-dependent kinases (Cdk), which are mainly controlled by transient interactions with cyclin regulatory subunits and by reversible phosphorylation (Morgan, 1997; Nigg, 1995). Among cyclins, cyclin A2 activates two different Cdk (Cdk1 and Cdk2) and hence participates in the regulation of both mitosis and M.A. Hayat (ed): Autophagy, Volume 11. DOI: http://dx.doi.org/10.1016/B978-0-12-805420-8.00005-6

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5. Role of Autophagy in Regulating Cyclin A2 Degradation: Live-Cell Imaging

S phase (Pagano et al., 1992). As such, cyclin A2 is a critical actor in the regulation of cell proliferation as well as essential in mouse early embryogenesis (Kalaszczynska et al., 2009; Murphy et al., 1997). It is also involved in the control of cell invasion (Arsic et al., 2012). Cyclin A2 accumulates from late G1 phase to mitosis. Cyclin A2 degradation occurs in mitosis and is required for chromosome alignment and anaphase progression (den Elzen and Pines, 2001; Geley et al., 2001). While most cyclin A2 is degraded by the ubiquitinproteasome system (UPS) (den Elzen and Pines, 2001; Geley et al., 2001; Sudakin et al., 1995), we have recently shown that autophagy also mediates cyclin A2 degradation (Loukil et al., 2014). Cyclin A2 degradation is also regulated by acetylation (Mateo et al., 2009). Cyclin A2 degradation is independent of the spindle assembly checkpoint (Di Fiore and Pines, 2010; Izawa and Pines, 2011; Wolthuis et al., 2008). Autophagy is a degradation pathway that eliminates misfolded, damaged, or superfluous cell components, whether individual molecules or organelles, into recycled pools of biomolecules. Characterized first as a general recycling process for defective structures, autophagy is now proposed to participate in regular cellular regulatory pathways (Boya et al., 2013). Here we present the general role of autophagy in protein turnover. We then focus on mitosis, where autophagy may be a failsafe mechanism. Finally, we provide an overview of our study on cyclin A2 degradation by autophagy, and further details on livecell imaging benefits.

AUTOPHAGY REGULATES PROTEIN TURNOVER Autophagy, also called macroautophagy, is a highly conserved catabolic process, which initiates with the formation of double layer membrane structures called phagophores. The phagophores elongate to engulf cytoplasmic organelles and macromolecular complexes and then form vesicles called autophagosomes (Kaur and Debnath, 2015; Yorimitsu and Klionsky, 2005). The autophagosomes fuse with lysosomes, inducing the digestion of their contents by hydrolases. Autophagy is important for degrading cytoplasmic contents such as organelles like mitochondria, macromolecular structures, and aggregated proteins. In addition, macroautophagy allows recycling of nutrients from macromolecules (Kaur and Debnath, 2015; Yorimitsu and Klionsky, 2005). Therefore, autophagy is a critical actor in cellular homeostasis. Autophagy not only is essential for the removal of damaged organelles, intracellular pathogens, and protein aggregates but also regulates selectively specific substrates. One of the selective aspects of autophagy is granted by cargo receptors such as p62/SQSTM1 and NBR1, which recognize ubiquitinylated targets (Kirkin et al., 2009; Lamark et al., 2009). Regarding autophagy significance in modulating signal transduction, it has been demonstrated that autophagy negatively regulates Wnt signaling by promoting Dishevelled (Dvl) degradation (Gao et al., 2010). The adaptor p62 facilitates the process of aggregation and the LC3-mediated autophagosome recruitment of Dvl, under starvation. Ubiquitylated Dvl aggregates are ultimately degraded through the autophagy-lysosome pathway (Gao et al., 2010). Furthermore, the selective aspect of autophagy can be independent of cargo receptors. Autophagy has been described to regulate cilia formation. It has been reported that autophagy is responsible for OFD1 (oral-facial-digital syndrome 1) removal at centriolar


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satellites, allowing the promotion of ciliogenesis in mammalian cells (Tang et al., 2013). All these findings define newly recognized roles of autophagy in signal transduction and organelle biogenesis via a coordinated degradation in time and space of specific proteins.

MITOTIC AUTOPHAGY, A FAILSAFE MECHANISM In this part, we focus on the role of autophagy in regulating mitotic factors under nutrient-rich conditions. For a deeper understanding of autophagy regulation, it is critical to assess the autophagy levels throughout the cell cycle, including mitosis. Cell division is a very dynamic step of the cell cycle. Mitosis drastically differs from the other cell cycle phases by the nuclear envelope breakdown and the inhibition of membrane traffic pathways (Jongsma et al., 2015; Lowe et al., 1998). Animal cells undergo mitosis in an open and continuous cellular compartment where the mitotic spindle and dividing chromosomes are in close proximity with organelles such as autophagosomes and lysosomes (Jongsma et al., 2015). Autophagic activity in mitosis is still unclear. While some groups have reported reduced autophagy in mitotic cells (Eskelinen et al., 2002; Furuya et al., 2010), another group has shown equal levels of autophagy during mitosis and interphase (Liu et al., 2009). It seems that autophagy levels are somehow decreased in mitosis, but not completely inhibited. This idea is actually supported by other studies where mitotic autophagy efficiently regulates specific substrates and macromolecular structures (see below) (Belaid et al., 2013; Loukil et al., 2014; Pohl and Jentsch, 2009). The lower activity of autophagy in mitosis seems to be controlled by Cdk1 and Cdk5. These kinases negatively regulate macroautophagy by phosphorylating a central regulator of autophagosome formation, the class III PtdIns3 kinase called Vacuolar protein sorting 34 (Vps34) (Furuya et al., 2010). Cdk1 and Cdk5 phosphorylate the Thr159 residue of Vps34, which inhibits its interaction with Beclin1 during mitosis as well as the production of phosphatidylinositol-3-phosphate (Furuya et al., 2010). Three examples about autophagy action in mitosis under conditions that are not nutritionally limiting are presented: RhoA degradation (Belaid et al., 2013), midbody ring (MR) disposal (Pohl and Jentsch, 2009) (below), and cyclin A2 degradation (Loukil et al., 2014) (next section). RhoA is a small GTPase that dictates cell shape and completion of cytokinesis via F-actin reticulation. The levels of active RhoA are finely tuned by autophagic degradation. An excess of active RhoA in the absence of autophagy is sufficient to induce aneuploidy, as a result of cytokinesis failure (Belaid et al., 2013). Under these conditions, active RhoA levels are dramatically increased at the midbody, followed by diffusion to the flanking zones. Under normal conditions, active RhoA is sequestered by p62 within autolysosomes and fails to localize to the plasma membrane or to the midbody. Consistently, a positive correlation has been found between autophagy defects and the higher expression of RhoA in human lung carcinoma (Belaid et al., 2013). Besides soluble proteins, selective autophagy can target macromolecular structures, such as the MR. The MR is a circular structure found at the end of cytokinesis within the intercellular bridge that connects the dividing cells (Pohl and Jentsch, 2009). Densely


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ubiquitylated, the MR is a target site for membrane delivery and considered to be a physical barrier between daughter cells. In telophase, the MR appears and localizes to the intercellular bridge during cytokinesis, and moves asymmetrically into one cell after abscission. Daughter cells usually do not accumulate MRs of previous divisions as they are discarded by autophagy, via their association with ubiquitin adaptor p62 and the ubiquitin-related protein Atg8 during abscission. Interestingly, accumulation of MRs has been associated with lysosomal storage disorders, indicating that defective MR disposal is characteristic of these diseases (Pohl and Jentsch, 2009). Thus, these studies point out a broader role of autophagy than previously assumed. Autophagy acts in mitosis by a fine and selective degradation of specific substrates including soluble proteins as well as large macromolecular structures. The extent of mitotic autophagy regulation is still unclear and not thoroughly studied, probably because of the short duration of mitosis and technical limitations.

MONITORING A NONCLASSICAL SUBSTRATE OF AUTOPHAGY, CYCLIN A2 We studied cyclin A2 degradation using high-resolution microscopic imaging, notably FRET (Förster or fluorescence resonance energy transfer) and FLIM (fluorescence lifetime imaging microscopy). Measurement of the near-field localization (at length scales comparable to the imaging wavelength) of protein complexes may be achieved by the detection of FRET between protein-conjugated fluorophores. FRET is a nonradiative, dipole–dipole coupling process whereby energy from an excited donor fluorophore is transferred to an acceptor fluorophore in close proximity (distance typically inferior to 10 nm) (Förster, 1948). Since the process depletes the excited state population of the donor, FRET will both reduce the fluorescence intensity and the fluorescence lifetime of the donor. The advantage of using donor FLIM to detect FRET, as opposed to intensity-based measurements, is due to the independence from fluorophore concentration and light path length. This approach is therefore well suited to studies in intact cells (see, e.g., Peter et al., 2005). Combined with confocal or multiphoton microscopical techniques to examine the localization of effects in cellular compartments, FLIM/FRET techniques allow the quantification of populations of interacting protein species on a point-by-point basis at each resolved voxel in the cell (Becker et al., 2001). Multiphoton microscopical techniques and in particular two-photon microscopy (Denk et al., 1990) confer particular advantages over confocal microscopy in the generation of three-dimensionally sectioned data. These advantages result from the use of intense nearinfrared light to induce nonlinear absorption in a probe fluorophore. The intensity dependence of the nonlinear absorption confines the excitation to a small volume in focal plane of the imaging lens. Photobleaching and photodamage are greatly reduced and imaging of sensitive live preparations is possible (Squirrell et al., 1999). We thus investigated cyclin A2 ubiquitylation by FRET measured by FLIM. MCF-7 cells were microinjected with vectors encoding cyclin A2-EGFP and ubiquitin-mCherry. In prometaphase, we observed FRET between cyclin A2-EGFP and ubiquitin-mCherry essentially in foci (Loukil et al., 2014). In metaphase, FRET occurred between cyclin A2 wt-EGFP and


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ubiquitin-mCherry in foci and elsewhere in the cell. Thus, our data indicate that cyclin A2 ubiquitylation occurs mainly in foci in prometaphase and spreads throughout the cell in metaphase. Cyclin A2-EGFP was used in numerous studies and proved to be a valuable tool reflecting faithfully the endogenous counterpart (den Elzen and Pines, 2001; Di Fiore and Pines, 2010; Jackman et al., 2003; Walker et al., 2008; Wolthuis et al., 2008). Nevertheless, to eliminate the possibility that the foci seen above were an artifact due to ectopic expression of cyclin A2-EGFP, we performed acquisitions by time-domain FLIM of MCF-7 cells immunostained for endogenous cyclin A2. We used two-photon excitation, trying to keep photobleaching to a minimum. By accumulating photons through time, we could actually detect several foci in mitotic cells (Loukil et al., 2014). The detection of these foci by confocal microscopy was more difficult and only possible with latest generation detectors, such as gallium-arsenide-phosphide (GaAsP) photomultiplier tubes (PMT). The FLIM detector and the GaAsP detector used for confocal images were of comparable sensitivity. However, FLIM acquisitions by two-photon microscopy could be longer than confocal acquisitions without yielding significant photobleaching. Moreover, FLIM images were calculated from the integrated number of counts for each pixel. We thus obtained highly contrasted images and very good signal to noise ratio. On the basis of these observations, we conclude that cyclin A2-rich foci indeed exist during mitosis and suggest that the lower sensitivity of the previous generation of microscopes precluded their detection. Dynamics of cyclin A2-rich foci were next studied, considering either cyclin A2-EGFP or endogenous cyclin A2. Cyclin A2-rich foci appeared similarly in all cell lines tested (MCF-7, MCF-10A, MDA-MB-231, U2OS) (Loukil et al., 2014). They were observed between prometaphase and telophase. They were located mainly at the periphery of the cells and moved in three dimensions. The presence of ubiquitylated forms of cyclin A2 in certain of these foci suggest that they could correspond to sites of degradation of the protein (Seeger et al., 2003). Indeed, in prometaphase, a colocalization of endogenous cyclin A2 was detected in foci with Cdc20, a key regulator of cyclin A2 ubiquitylation. Furthermore, a few cyclin A2 foci colocalized with active proteasomes (Loukil et al., 2014), identified by the rapid digestion of microinjected DQ-ovalbumin (Baldin et al., 2008; Rockel et al., 2005). Thus, our data suggest that at least some of the foci could be sites of both ubiquitylation and proteasomal degradation. However, it was clear that not all cyclin A2 foci colocalized with Cdc20 or DQ-ovalbumin. Furthermore, it is striking that some cyclin A2 foci persist until late mitosis, i.e., after most proteasomal degradation of cyclin A2 has occurred. We therefore hypothesized that cyclin A2 degradation might also involve another pathway. Since autophagy is another major process for intracellular proteolysis, we investigated whether it contributes to cyclin A2 degradation. First, we used bafilomycin A1 (BFA), a lysosomal proton pump inhibitor that raises the lysosomal pH (Yoshimori et al., 1991) and thus inhibits the autophagosome–lysosome fusion step and autophagy flux (Yamamoto et al., 1998), thereby identifying potential substrates. In MCF-7 cells treated with BFA, some endogenous cyclin A2 foci colocalized with light chain 3-B protein (LC3-B), a marker of autophagosomes, in metaphase cells (Loukil et al., 2014). In addition, we detected colocalization of some cyclin A2 foci with p62, a receptor for ubiquitylated proteins necessary for their degradation by selective autophagy (Pankiv et al., 2007), that is stabilized by BFA


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treatment (Bjørkøy et al., 2005). Moreover, many cyclin A2-EGFP foci colocalized with lysosomes, stained with Lysotracker. We also detected colocalization between cyclin A2-EGFP foci and LC3-B-mCherry (Loukil et al., 2014). Importantly, careful analysis of endogenous cyclin A2 distribution showed that its foci colocalized with either LC3-B or DQ-ovalbumin, suggesting that the foci comprise at least two different populations, each linked to distinct degradation pathways. In fact, our data suggest that, in prometaphase, cyclin A2 foci colocalized mainly with Cdc20 or DQ-ovalbumin, while in metaphase, they colocalized mainly with LC3-B, p62, or lysosomes. To estimate the relative contributions of UPS versus autophagy in cyclin A2 degradation, synchronized MCF-7 cells were treated with either epoxomicin, a proteasome inhibitor, or BFA, and the two together. Quantification by immunofluorescence of the levels of endogenous cyclin A2 in metaphase cells showed a significant increase in cyclin A2 levels after either treatment, where that seen with BFA was lower than epoxomicin (Loukil et al., 2014). This indicates that both pathways contribute to cyclin A2 degradation. The fact that the two inhibitors showed additive effects further suggests that the two pathways function in parallel in this process. To confirm the contribution of autophagy in cyclin A2 degradation, we used a shRNA directed against autophagy-related protein 7 (Atg7), an E1-like activating enzyme required for autophagosome formation (Tanida et al., 2001). We then evaluated the level of endogenous cyclin A2 in metaphase cells. Following introduction of the Atg7 shRNA expression vector in MCF-7 cells, p62 levels increased, confirming the expression of Atg7 shRNA. In parallel, cyclin A2 level increased in metaphase cells (Loukil et al., 2014). Similar results were obtained with MCF-10A cells using this Atg7 shRNA vector. These data are consistent with a role for autophagy in cyclin A2 degradation. We next resorted to an U2OS cell line stably transfected with an inducible expression vector for cyclin A2-EGFP to study its degradation by time lapse microscopy. In the presence of the Atg7 shRNA expression vector, cells displayed slower cyclin A2 degradation. Notably, this defect was partially rescued by expressing a shRNA-resistant form of Atg7. Moreover, we induced autophagy by starving U2OS cells expressing cyclin A2-EGFP in EBSS medium. Indeed, this led to an increase in LC3-B puncta detected by immunofluorescence (Loukil et al., 2014). Under these conditions, cyclin A2-EGFP was degraded more rapidly than in control cells incubated with normal medium. This further confirmed that autophagy contributes to cyclin A2 degradation. Furthermore, inhibition of autophagy by Atg7 shRNA led to prolonged mitosis in U2OS cells and in MCF-7 cells. Prometaphase and metaphase were particularly delayed, which reflects effects on cyclin A2 degradation, in agreement with the literature (den Elzen and Pines, 2001), as well as possibly other unidentified substrates. Again, this defect was partially rescued by expressing a shRNA-resistant form of Atg7. Moreover, the mitotic delay observed in Atg7 shRNA treated cells was partially rescued by treatment with cyclin A2 shRNA (Loukil et al., 2014). Our data demonstrate for the first time that autophagy is involved in cyclin A2 degradation. We believe that this discovery is important since regulation of cyclin degradation is crucial for coordinating progression through the cell cycle. Indeed, we observed that inhibition of autophagy by Atg7 shRNA leads to prolonged mitosis and that cyclin A2 depletion rescues this phenotype.


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DISCUSSION UPS and autophagy are both critical for cellular homeostasis and their activities are carefully orchestrated (Schreiber and Peter, 2014). Recent evidence has revealed cross-talk mechanisms involving small ubiquitin ligand molecules and the linking protein p62, as well as cell signaling pathways and transcription factors (Lilienbaum, 2013). Indeed, the two degradation pathways use common adaptor and regulatory molecules. Several proteins, and especially kinases and transcription factors, have already been shown to be located at the interface between both degradation pathways. Various proteins are degraded by both pathways, UPS and autophagy, such as α-synuclein (Webb et al., 2003), β-catenin, httQ74 huntingtin mutant (Korolchuk et al., 2009), dishevelled (Gao et al., 2010). Our data show that UPS and autophagy contribute to cyclin A2 degradation. We do not know the precise role of autophagy in cyclin A2 degradation; it could be a safeguard mechanism to increase cyclin A2 degradation. Nevertheless, we demonstrate that even if the fraction of cyclin A2 degraded by autophagy is low, this phenomenon is important since it plays a role in mitosis duration. Our results add another component to the complex regulatory network that involves UPS and autophagy as cooperative and complementary processes to maintain cellular homeostasis.

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C H A P T E R

6 Roles of Rab-GAPs in Regulating Autophagy Takashi Itoh and Mitsunori Fukuda O U T L I N E Introduction 144 Roles of Rab-Type Small GTPases in Membrane Trafficking 144 Membrane Remodeling in Autophagy 146

TBC1D25/OATL1 150 Rab3GAP1 and Rab3GAP2 151 Other Rab-GAPs Possibly Involved in Autophagy 151

RAB-GAPs Involved in Autophagy 147 TBC1D2/Armus 147 TBC1D5 147 TBC1D14 148 TBC1D15 and TBC1D17 149

Discussion 152 Acknowledgments 154 References 154

Abstract

Autophagy maintains intracellular homeostasis by degrading unfavorable components and thereby supplying nutrients for renovation. During autophagy, double-membrane structures called isolation membranes form and elongate to surround the components to be degraded. The resulting closed spherical structures, called autophagosomes, then fuse with endosomes and lysosomes. Since autophagosomes are membranous structures, it is generally thought that a membrane supply from other organelles to isolation membranes is necessary to form autophagosomes. Membrane trafficking is a fundamental system by which organelles (or vesicles) are formed and by which proper communication between organelles is achieved, and a variety of proteins that are required for membrane trafficking have been identified and their roles determined in the past few decades. However, involvement of such proteins in autophagy was largely unknown for a long time. Recent studies have shown that Rab small GTPases, which are key regulators of membrane trafficking, play important roles in autophagy, and several Rab-GAPs (GTPase-activating proteins), negative regulators of Rabs, have been reported to be involved in autophagosome formation and maturation. In this chapter we provide an overview of the proposed functions of Rab-GAPs and discuss both their relation to the current model of autophagosome formation and maturation and the future Rab-GAP research.


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6. ROLES OF RAB-GAPs IN REGULATING AUTOPHAGY

INTRODUCTION Roles of Rab-Type Small GTPases in Membrane Trafficking The internal structures of eukaryotic cells consist of small membranous compartments called organelles. There are many kinds of organelles, each having its own characteristics that are determined by the specific proteins and lipids that compose the organelles. Possessing these characteristics enables organelles to perform unique functions that are required to conduct various cellular activities, but they are not totally independent, and they communicate with each other. For example, proteins to be secreted are transported into the endoplasmic reticulum (ER), traveled through the Golgi apparatus where they are modified with sugars, and are finally sorted to the plasma membrane where they are exocytosed. Eukaryotic cells have a sophisticated mechanism for organelle (or vesicle) biogenesis and transport called “membrane trafficking.” Membrane trafficking is generally achieved in the following four steps: (1) membrane budding at a donor organelle and formation of a vesicle; (2) transport of the vesicle; (3) tethering/docking of the vesicle to an acceptor organelle; and (4) fusion between vesicle and acceptor organelle (Stenmark, 2009). A number of mechanical factors (e.g., formation of membrane curvature, pinching off of the vesicle from the donor organelle, transport of the vesicle along cytoskeletons) and trafficking regulators, including Rab-type small GTPases, that regulate these steps have been identified. The Rab family is conserved in all eukaryotic cells, and the human genome contains over 60 Rab genes. Each Rab protein is thought to regulate a specific membrane trafficking route (or step) (Fukuda, 2008; Stenmark, 2009). The Rab family are members of the Ras superfamily and act as molecular switches by binding GTP (active state) or GDP (inactive state). Since activated Rabs have to interact with an “effector” protein to fulfill their function at the proper time and place, fine-tuning Rab activity is important for membrane trafficking. Rab activation and inactivation are accomplished by guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs), respectively, the same as other small GTPases (Barr and Lambright, 2010) (Fig. 6.1A). GEFs release guanine nucleotides from Rabs irrespective of GTP or GDP, and the nucleotide-free Rabs then bind new guanine nucleotides according to the population of GTP and GDP in the cytosol (GTP:GDP = 1000:1), resulting in activation of the Rabs. By contrast, GAP promotes the intrinsic GTPase activity of Rabs, resulting in an increase in GDP-bound Rabs. The Tre-2/Bub2/Cdc16 (TBC) domain is a conserved domain in eukaryotic species, and most of the TBC domains analyzed thus far have been shown to possess GAP activity toward certain Rabs (Fig. 6.1B). The TBC domain contains two catalytic residues, arginine and glutamine, that are responsible for its GAP activity, and consequently this unique mechanism of action is referred to as the “dual finger mechanism” (Pan et al., 2006). More than 40 genes that encode TBC domain–containing proteins (TBC proteins) have been identified in the human genome and the target Rab proteins of about half of them have yet to be identified (Fukuda, 2011; Frasa et al., 2012). GEFs and GAPs are thought to control Rabs by being regulated by an upstream signal(s), for example, environmental changes. However the entire signaling cascades of the majority of Rabs remain to be determined.


Introduction

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FIGURE 6.1 A Rab-type small GTPase and its inactivator GAP. (A) Schematic model of the function of Rab and its regulators (effector, GEF, and GAP) in membrane trafficking. (B) Domain organization of human TBC proteins that have been shown to be involved in autophagy. Small red regions indicate the LIR. GAP, Rab3GAP2_N, and Rab3GAP2_C are domains conserved in orthologues of different species. Rab-GAP interactors and their interacting regions are indicated on each molecule. CC, coiled-coil; PH, pleckstrin homology; TBC, Tre-2/Bub2/Cdc16; GAP, GTPase-activating proteins; GEF, guanine nucleotide exchange factor; and LIR, LC3-interacting region.


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Membrane Remodeling in Autophagy Autophagy is a conserved intracellular degradation system in eukaryotic cells. Autophagy is activated by several stresses, including starvation, during which cells need to obtain nutrients by randomly degrading their own proteins and organelles to survive (Mizushima et al., 2011). On the other hand, intracellular homeostasis is sometimes only maintained by degradation of specific organelles (e.g., damaged organelles) and protein aggregates by autophagy, and this kind of autophagy is called “selective autophagy” (Stolz et al., 2014). Accordingly, defects of autophagy lead to human diseases such as neurodegenerative diseases, immune diseases, and cancer (Jiang and Mizushima, 2014). During autophagy, intracellular materials are transported to lysosomes where they are degraded by digestive enzymes. Autophagy is accomplished by the formation and maturation (degradation) of autophagosomes, which are unique, transient organelles that contain cytoplasmic materials within their double-membrane structure. Membranous structures called isolation membranes (also called phagophores) elongate and engulf a portion of cytoplasm, and their leading edges ultimately fuse to form spherical autophagosomes. How membranes are supplied to isolation membranes is a longstanding question. Although many organelles, including the ER, mitochondria, plasma membrane, and recycling endosomes have been proposed as possible sources of isolation membranes, their exact source remains unknown (Ge et al., 2014; Shibutani and Yoshimori, 2014; Carlsson and Simonsen, 2015). Autophagosomes maturate, on the other hand, by fusing with endosomes and lysosomes, where their contents are degraded. Autophagosomes fuse with endosomes and lysosomes by both the unique mechanism for the autophagic pathway and the common mechanism for the endocytic pathway (Itakura and Mizushima, 2013). Genes essential for autophagy (ATG) were discovered by yeast genetic analyses (Ohsumi, 2014), and the functions of the product of each of the genes have gradually been identified (Nakatogawa et al., 2009; Mizushima et al., 2011). Atg proteins are classified into the following six groups: (1) the Atg1/ULK1 kinase complex; (2) the class III PI3 kinase complex; (3) the Atg12 conjugation system; (4) the Atg8 family protein conjugation system; (5) the Atg2-Atg18 complex; and (6) Atg9, the sole transmembrane protein. Atg12 and Atg8 family proteins, including Atg8 in yeasts and LC3s and GABARAPs in mammals, are ubiquitinlike proteins and are conjugated to Atg5 and phosphatidylethanolamine (PE), respectively. The amount of PE-conjugated Atg8 family proteins (PE-conjugated LC3, which is referred to as LC3-II) is a widely used indicator of autophagic activity (Klionsky et al., 2012). Most Atg proteins play pivotal roles in the formation of autophagosomes and are localized at isolation membranes and/or autophagosomes. Even though the core ATG genes essential for autophagy have already been identified and the functions of the Atg proteins have gradually been determined, the mechanism and regulation of membrane remodeling in autophagy are almost completely unknown. Recent studies have suggested the involvement of membrane trafficking factors in both autophagosome formation and maturation, and several groups have reported the functions of Rabs and Rab-GAPs in autophagy (Ao et al., 2014; Szatmári et al., 2014; Amaya et al., 2015; Kern et al., 2015; Chua and Tang, 2015). In this chapter we will focus on Rab-GAPs and their substrate Rabs that have been reported to be involved in autophagy.


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RAB-GAPs INVOLVED IN AUTOPHAGY TBC1D2/Armus TBC1D2/Armus was originally identified as a protein that interacts with Rac1, a Rhotype small GTPase responsible for remodeling the actin cytoskeleton (Frasa et al., 2010) (Fig. 6.1B). TBC1D2/Armus acts as an effector of Rac1 and regulates the degradation of E-cadherin, an important protein for cell–cell contact (adherens junctions), in lysosomes through the endocytic pathway. Braga’s group has proposed that TBC1D2/Armus regulates E-cadherin turnover by inactivating Rab7, a Rab important for lysosomal homeostasis. Since Rab7 is also important for autophagosome maturation, the same group has also proposed that TBC1D2/Armus is involved in autophagy (Carroll et al., 2013). They found that TBC1D2/Armus is localized at autophagosomes and interacts with LC3, one of the Atg8 family proteins in mammals. Their study showed that overexpression of TBC1D2/ Armus increased the amount of LC3-II, an indicator of autophagic activity described above. The autophagosomal localization, the interaction with LC3, and the phenotype induced by overexpression of TBC1D2/Armus entirely depend on its N-terminal half, which is where it interacts with Rac1. Interestingly, knockdown of TBC1D2/Armus in keratinocytes has been found to increase the amount of activated Rab7 and delay autophagosome maturation (i.e., fusion between autophagosomes and lysosomes) under starved conditions, although the knockdown did not result in an increase in the number of autophagosomes. Since Rac1 is inactivated under starved conditions, it has been proposed that Rab7-GAP TBC1D2/ Armus plays a role with Rac1 in endocytosis under nutrient-rich conditions and with LC3 in autophagy under starved conditions (Carroll et al., 2013). However, since E-cadherin functions mainly in epithelial cells, the Rac1-TBC1D2/ Armus-LC3 system may not function in other cell types. Actually, in contrast to its autophagosomal localization in keratinocytes (Carroll et al., 2013), GFP-tagged TBC1D2/ Armus has been shown not to colocalize with LC3B in MEFs (mouse embryonic fibroblasts) or HeLa cells (Itoh et al., 2011; Popovic et al., 2012). Thus, it is highly possible that the function of TBC1D2/Armus is cell-type specific and that other Rabs and Rab-GAPs are involved in autophagosome–lysosome fusion in other cell types (see “TBC1D25/OATL1” section). TBC1D2/Armus has a homologue called TBC-2 in Caenorhabditis elegans that functions in phagocytosis by inactivating Rab5, not Rab7 (Chotard et al., 2010). Since TBC-2 also interacts with Rac1 the same as TBC1D2/Armus does (Sun et al., 2012), the function of TBC-2/ TBC1D2 as a Rac1 effector must have been conserved during evolution. It will be interesting to learn whether C. elegans TBC-2 mutants exhibit defects in autophagy in future studies.

TBC1D5 TBC1D5 was originally reported to be a factor involved in endosome-to-Golgi trafficking through interaction with a retromer complex (Seaman et al., 2009). TBC-5, a C. elegans orthologue of TBC1D5, has been shown to possess GAP activity toward Rab7 and function in endocytosis (Mukhopadhyay et al., 2007), and overexpression of TBC1D5 in mammalian cells has been found to cause dissociation of Rab7 from membranes, suggesting that


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TBC1D5 inactivates Rab7 (Seaman et al., 2009). Subsequent screening for TBC domains that interact with the Atg8 family proteins LC3A and GABARAPL1 revealed the presence of 14 candidate TBC proteins, including TBC1D5, which shows less colocalization with LC3 (Popovic et al., 2012). TBC1D5 has two independent LC3-interacting region (LIR) motifs, which are important for interactions with Atg8 family proteins and colocalization with LC3B (Fig. 6.1B). Interestingly the N-terminal LIR is also responsible for its interactions with the retromer complex, and the retromer complex and Atg8 family proteins compete with each other for binding to the LIR. Since TBC1D5 is translocated from a retromer-complex-positive compartment to an LC3B-positive compartment by starvation, it has been proposed that TBC1D5 changes its function from endosomal trafficking to autophagosome formation when autophagy is induced. Despite implicating that TBC1D5 possesses GAP activity toward Rab7, knockdown of TBC1D5 suppressed autophagosome formation, rather than autophagosome maturation. A subsequent study by the same group has shown that TBC1D5 is involved in autophagosome formation by regulating trafficking of Atg9, an essential factor for autophagosome formation (Popovic and Dikic, 2014). However the physiological significance of its interaction with LC3 via LIRs and its GAP activity in autophagy is still unclear, because all that is known is that these LIRs are required for its recruitment to LC3-positive structures.

TBC1D14 TBC1D14 was identified by screening for TBC proteins whose overexpression decreased the amount of LC3-II (Longatti et al., 2012). Consistent with previous reports that overexpression of TBC1D14 induces Golgi fragmentation and mislocalization of the Shiga Toxin B subunit at recycling endosomes independently of its GAP activity (Fuchs et al., 2007; Haas et al., 2007), a catalytic GAP domain mutant of TBC1D14 has been found to decrease the amount of LC3-II to the same extent as the wild-type, indicating that its effect on autophagy is independent of its GAP activity. Longatti et al. tested 47 Rabs in a search for a TBC1D14 substrate, but none tested positive. Instead, they found that TBC1D14 interacts with Rab11 (Fig. 6.1B), which is involved in recycling endosome trafficking (Ullrich et al., 1996) as well as in autophagy. However the role of Rab11 in autophagy is somewhat controversial: it is involved in autophagosome formation (Knævelsrud et al., 2013) versus fusion between autophagosomes and late endosomes/multivesicular bodies (Fader et al., 2008, 2009; Szatmári et al., 2014). Data obtained by Longatti et al. supported a role of Rab11 in autophagosome formation because expression of dominant negative Rab11 suppresses autophagic flux. Since TBC1D14 interacts with active Rab11 and is localized at recycling endosomes in a Rab11-dependent manner, TBC1D14 is likely to function as an effector of Rab11 during autophagy. However, its function may not be so simple, because knockdown of TBC1D14 promotes, whereas overexpression inhibits, autophagosome formation (i.e., TBC1D14 knockdown and Rab11 inactivation have opposite effects). In addition to interacting with Rab11, TBC1D14 are associated with two different autophagic proteins. It directly interacts with the Atg protein ULK1 and tethers ULK1 at recycling endosomes (Longatti et al., 2012). It has been proposed that TBC1D14 attenuates autophagosome formation by tethering ULK1 at recycling endosomes under fed conditions, whereas TBC1D14 translocates from recycling endosomes to the trans-Golgi network (TGN)



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and enables ULK1 and Rab11 function in autophagosome formation under starved conditions. TBC1D14 also interacts with a TRAPPIII complex (Rab1-GEF) and regulates Atg9 trafficking via Rab1 activation (Lamb et al., 2016). Thus, TBC1D14 is likely to be an important hub in the regulation of autophagy signaling.

TBC1D15 and TBC1D17 Mitophagy is a kind of selective autophagy in which damaged mitochondria are degraded. Damaged mitochondria are harmful to cells, and there is a mechanism that clears damaged mitochondria and is mediated by Parkin E3 ubiquitin ligase (Pickrell and Youle, 2015). A proteomic approach to identifying Parkin substrates has revealed that TBC1D15 is a Parkin substrate (Sarraf et al., 2013). Several other characteristics of TBC1D15 have already been reported (Fig. 6.1B): (1) TBC1D15 is localized at the surface of mitochondria through interaction with Fis1, a mitochondrial outer membrane protein (Onoue et al., 2013); (2) TBC1D15 interacts with Atg8 family proteins (Behrends et al., 2010); and (3) Rab7 is a target of TBC1D15 (Zhang et al., 2005). Yamano et al. (2014) recently showed that knockout of TBC1D15 inhibits clearance of mitochondria damaged by valinomycin, a mitochondrial depolarizing drug, and that it accumulates abnormal LC3-positive aggregates in the cytosol, indicating that TBC1D15 is involved in mitophagy. All three characteristics of TBC1D15 listed above are essential for the function of TBC1D15 in mitophagy, whereas TBC1D15 does not seem to be essential for starvation-induced autophagosome formation. Since knockdown of Rab7 suppresses the accumulation of LC3-positive aggregates by knockout of TBC1D15, TBC1D15 is likely to act through inactivation of Rab7 in mitophagy. The function of Rab7 is not required for starvation-induced autophagosome formation, because downregulation of Rab7 resulted in the accumulation of autolysosomes, which are formed by fusion between autophagosomes and lysosomes (Jäger et al., 2004; Gutierrez et al., 2004). This phenotype is distinct from the loss of Ypt7, a yeast counterpart of Rab7, which leads to a defect in the fusion between autophagosomes and the vacuole (yeast lysosome) (Kirisako et al., 1999). The finding that Rab7 is involved in the transformation of autolysosomes into lysosomes (Yu et al., 2010) may explain why downregulation of Rab7 results in the accumulation of autolysosomes. On the other hand, Rab7 is required for the formation of autophagosomes that engulf invasive bacteria during xenophagy, another kind of selective autophagy (Yamaguchi et al., 2009). During selective autophagy the isolation membranes have to elongate farther to enclose the target for degradation and form larger autophagosomes than in canonical starvation-induced autophagy, suggesting that Rab7 is required for greater extension of the isolation membranes. Therefore TBC1D15 is likely to function specifically in mitophagy by regulating Rab7 activity in the process that extensively elongates isolation membranes toward damaged mitochondria. TBC1D17 is a homologue of TBC1D15 that forms a homodimer and a heterodimer with TBC1D15, and it also participates in mitophagy (Yamano et al., 2014). TBC1D17 has recently been reported to play a role in starvation-induced autophagy and cell death together with optineurin, which is an autophagy adaptor (Chalasani et al., 2014; Sirohi and Swarup, 2016). However, since Rab8, a possible target of TBC1D17 (Vaibhava et al., 2012), is dispensable for starvation-induced autophagy (Amagai et al., 2015), whether the GAP activity of TBC1D17 is involved in starvation-induced autophagy is unclear.


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TBC1D25/OATL1 We have identified TBC1D25/OATL1 as an uncharacterized TBC protein at autophagosomes by screening for GFP-tagged Rab-GAPs that colocalize with endogenous LC3. TBC1D2B and OATL1 were the only two of the TBC proteins and Rab3GAP1 tested that were found to fully colocalize with LC3B and TBC1D11 to partially colocalize with LC3B (Itoh et al., 2011). OATL1 was localized at autophagosomes through interaction with Atg8 family proteins via its LIR (Fig. 6.1B). Unlike p62/sequestosome 1, another LC3-binding protein known to be an efficient substrate of autophagy, OATL1 is not degraded by autophagy by specifically recruiting outside the autophagosomes (LC3B and p62 reside both inside and outside the autophagosomes) (Hirano et al., 2016). Overexpression of OATL1 in MEFs was found to inhibit fusion between autophagosomes and lysosomes in a GAP-activity-dependent and Atg8-family-protein-binding activity-dependent manner (Fig. 6.2). Rab2A and Rab33B, which interacts with Atg16L1, an essential component of isolation membrane elongation (Itoh et al., 2008; Ishibashi et al., 2011), are the only substrates of TBC1D25 that have been identified

FIGURE 6.2 Overexpression of OATL1 in MEFs attenuated autophagosome maturation in a GAP-activitydependent manner. Typical images of cells expressing EGFP-LC3 alone (control), both EGFP-LC3 and T7-OATL1 (wild-type), and both EGFP-LC3 and T7-OATL1-RK (GAP-activity-deficient mutant) are shown. Replenishment of nutrients clearly resulted in a decrease in the number of EGFP-LC3 dots (corresponding to autophagosomes) in the control cells and T7-OATL1-RK cells, while a large number of EGFP-LC3 dots remained in the T7-OATL1 cells. The number and distribution of EGFP-LC3 dots in MEFs expressing T7-OATL1-WA (LC3-binding-deficient mutant) is similar to the numbers in the control cells and T7-OATL1-RK cells (data not shown; see Itoh et al., 2011). Scale bars = 20 μm. MEFs, mouse embryonic fibroblasts; GAP, GTPase-activating proteins.



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thus far (Itoh et al., 2006, 2011). Overexpression of an active-form fixed mutant of Rab33B in MEFs also inhibited the same fusion process, strongly suggesting that the target of TBC1D25 in autophagy is Rab33B. However, even though TBC1D25 overexpression inactivates endogenous Rab33B, neither knockdown of Rab33B nor OATL1 in MEFs affected autophagic flux. Thus, we cannot rule out the possibility of TBC1D25 having another substrate(s) that is involved in autophagosome maturation, or the existence of a redundant pathway(s).

Rab3GAP1 and Rab3GAP2 Rab3GAP1 (catalytic subunit) and Rab3GAP2 (noncatalytic subunit) were originally purified from brain cell lysates as proteins that exhibit GAP activity toward Rab3 (Fukui et al., 1997; Nagano et al., 1998). Neither Rab3GAP1 nor Rab3GAP2 contain a TBC domain, but their domain organization and GAP activity toward Rab3 are conserved in animals (Fig. 6.1B). It has recently been independently demonstrated that loss of Rab3GAP1 in C. elegans (Spang et al., 2014) and fly muscle (Zirin et al., 2015) results in a defect in autophagy, and Rab3GAP1/2 have been shown to modulate autophagy in mammalian primary fibroblasts (Spang et al., 2014). Interestingly, knockdown of Rab3GAP1 impaired the formation of LC3-positive structures, whereas knockdown of Rab3 or expression of active Rab3 did not affect it, suggesting that Rab3GAP1/2 participate in autophagy independently of its Rab3-GAP activity. Spang et al. further showed that knockdown of Rab3GAP1 did not affect the formation of Atg5-positive isolation membranes and suggested a role of Rab3GAP1/2 in the LC3 lipidation step, although the precise mechanism by which Rab3GAP1 regulates LC3 lipidation remains unknown. Human genetics studies have revealed that mutations in either Rab3GAP1 or Rab3GAP2 result in Warburg Micro syndrome, a genetic disorder with severe eye and brain abnormalities (Handley et al., 2015). Analyses of Warburg Micro syndrome have linked the Rab3GAP complex to Rab18 and TBC1D20, because mutations in either gene resulted in the same syndrome (Handley et al., 2015). Surprisingly the Rab3GAP complex possesses GEF activity toward Rab18 (Gerondopoulos et al., 2014). TBC1D20 was originally identified as an ER-resident TBC protein that is involved in maintaining Golgi integrity through inactivation of Rab1 (Haas et al., 2007). Although TBC1D20 exhibits slight GAP activity toward Rab18 in vitro (Haas et al., 2007), loss of TBC1D20 affects the localization of Rab18 at the ER (Handley et al., 2015), suggesting that Rab18 is a target of TBC1D20 in vivo. Another common feature of Rab3GAP1/2, Rab18, and TBC1D20 is localization at lipid droplets derived from the ER (Ozeki et al., 2005, Nevo-Yassaf et al., 2012, Spang et al., 2014). Since the lipid droplets are organelles with a close relationship with autophagosomes (Deretic, 2015), these proteins may function together at lipid droplets in autophagosome formation. However, there is no direct evidence that Rab18 and TBC1D20 participate in autophagy. Future investigations of the functional relationships between Rab3GAP1/2, Rab18, and TBC1D20 in autophagy will reveal the precise mechanism of autophagosome biogenesis.

Other Rab-GAPs Possibly Involved in Autophagy Autophagy is regulated by a conserved protein kinase complex, mTORC1 (mammalian target of rapamycin complex 1) (Bar-Peled and Sabatini, 2014; Shimobayashi and Hall, 2016). The small GTPase Rheb activates mTORC1 in response to growth factors (Dibble and


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Cantley, 2015). A TSC complex that is comprised of TSC1, TSC2, and TBC1D7 is a Rheb GAP (Dibble et al., 2012). Interestingly, although TBC1D7 is essential for the integrity of the TSC complex, TBC1D7 itself does not inactivate Rheb (TSC2 is a catalytic subunit). It should be noted that the two catalytic residues, arginine and glutamine, in the TBC domain of TBC1D7 are not conserved, suggesting that TBC1D7 is an “inactive GAP,” at least in the mTORC1 pathway. This suggestion is supported by the fact that the fruit fly (Drosophila melanogaster) has a counterpart of TBC1D7 that has little homology to mammalian TBC1D7 and is not recognized as a TBC protein (Glatter et al., 2011). Interestingly, even though TBC1D7 lacks key catalytic residues, TBC1D7 has been shown to be involved in primary cilium formation through inactivation of Rab17 (Yoshimura et al., 2007). Furthermore, Rab17 regulates the membrane supply from recycling endosomes, where Rab17 is localized, to the autophagosomes that surround bacteria during xenophagy (Haobam et al., 2014). Thus, it will be very interesting to investigate the contribution of Rab17 and TBC1D7 to autophagosome formation in other types of autophagy, including starvation-induced autophagy. Rab1 and Ypt1, a yeast counterpart of Rab1, are involved in autophagosome formation, although their molecular functions are debated (reviewed in Ao et al., 2014). TBC1D20 was originally characterized as a Rab1-GAP (Haas et al., 2007), and there is some evidence in support of Rab1 and TBC1D20 functioning in the same pathway, especially for virus replication (Sklan et al., 2007; Zenner et al., 2011). Thus, TBC1D20 (or other unidentified Rab-GAPs) may regulate autophagosome formation by inactivating Rab1. Alternatively, TBC1D20 may be involved in autophagosome formation by inactivating Rab18 as described earlier. TBC1D11/RabGAP1/GAPCenA is partially colocalized with LC3B (Itoh et al., 2011) but completely colocalized with Atg16L1, an isolation membrane marker protein (Itoh and Fukuda, unpublished data), indicating that TBC1D11 is localized at isolation membranes. Such localization of TBC1D11 may be dependent on interactions with Atg8 family proteins, ULK1, and/or WIPI2 (Behrends et al., 2010; Popovic et al., 2012; Huttlin et al., 2015). Furthermore, knockdown of the TBC1D11 orthologue in fly muscle was found to suppress autophagosome formation (Zirin et al., 2015), suggesting that TBC1D11 may function in autophagosome formation. Further study will be necessary to elucidate the molecular mechanism by which TBC1D11 regulates autophagosome formation.

DISCUSSION Autophagy is thought to be a dynamic degradation system that involves almost all organelles. The ER, plasma membrane, mitochondria, lipid droplets, the Golgi apparatus, and recycling endosomes have actually been proposed to be sources of the membranes involved in autophagosome formation. Endosomes and lysosomes fuse with autophagosomes during autophagosome maturation (Shibutani and Yoshimori, 2014; Carlsson and Simonsen, 2015). Therefore the mechanism that regulates the membrane remodeling in autophagy must be complicated. The forward approach to investigating the functions of Atg proteins has revealed the functional relationship between Atg proteins. However, little is known about the regulation of membrane remodeling by Atg proteins, mainly because Atg proteins do not contain any factors that are known to be involved in membrane trafficking. On the other hand, the reverse approach, i.e., by studies that investigate the involvement of membrane


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trafficking proteins in autophagy, is now shedding light on the contribution of other organelles to autophagy. Actually, several studies have revealed involvement of Rabs and the organelles on which they reside in autophagy (Ao et al., 2014; Szatmári et al., 2014; Amaya et al., 2015; Chua and Tang, 2015). In this chapter we have provided an overview of the RabGAPs that have been proposed to regulate various steps of autophagy. TBC1D5, TBC1D14, and Rab3GAP1/2 are involved in the autophagosome formation step, whereas TBC1D2 and TBC1D25 are involved in the autophagosome maturation step, and TBC1D15 and TBC1D17 are likely to be specific for mitophagy. However, their proposed functions and mechanisms need to be verified in the future. Below we point out some difficulties and problems in autophagy research for future verification. One of the difficulties in understanding the complexity of membrane remodeling in autophagy is behavior of Atg9, because Atg9 is essential for autophagosome formation and travels between the TGN and endosomes, which are also important for autophagosomal maturation (Zavodszky et al., 2013). TBC1D2, TBC1D5, and TBC1D14 have already been reported to be involved in the endocytic pathway (Haas et al., 2007; Seaman et al., 2009; Frasa et al., 2010; Lamb et al., 2016). Gene manipulation of TBC1D5 has actually been shown to result in a change in Atg9 trafficking (Popovic and Dikic, 2014). Although the precise mechanism of Atg9 trafficking is largely unknown, Rab-GAPs involved in endosomal trafficking must alter autophagosome formation by changing Atg9 trafficking. Moreover, endocytosis defects tend to impair lysosomal homeostasis, which leads to changes in autophagic flux (Klionsky et al., 2012). Thus, careful evaluation is required to determine whether the effects of endocytic Rab-GAPs are specific to autophagy or not. Another difficulty is differences in experimental conditions, because autophagy is induced by several stresses (e.g., certain experimental conditions may affect autophagic flux). Actually, there have been many contradictory results of research on the role of Rab-GAPs in autophagy. For example, whether Rab-GAPs colocalize with autophagy proteins is a matter of controversy. Popovic et al. and Itoh et al. performed a large-scale screening experiment to identify Rab-GAPs that are localized at autophagosomes and found that TBC1D2B and TBC1D25/ OATL1 clearly colocalized with LC3B, whereas TBC1D2/Armus, TBC1D5, TBC1D14, TBC1D15, and TBC1D17 were not identified as clear autophagosomal residents by the screening experiment (Itoh et al., 2011; Popovic et al., 2012). The results of overexpression or knockdown studies of Rab-GAPs are also controversial. For example, overexpression of TBC1D5 reduced the amount of LC3-II (Longatti et al., 2012) in contrast to the report by Popovic et al. (2012), and knockdown of TBC1D25 showed different effects on the number of LC3 dots (Itoh et al., 2011; McKnight et al., 2012). These differences in results may be attributable to the different experimental conditions, for example, use of different cell lines or tagged proteins versus endogenous proteins. Using proper methods and appropriate interpretation of the results obtained (Klionsky et al., 2012) will be helpful in resolving such conflicting results. Two different assay methods, in vitro GAP assay and pull-down GAP assay, are often used to measure GAP activity. Purified recombinant Rab and Rab-GAP proteins from bacteria or mammalian cells are used to perform in vitro GAP assays, and the amount of GTP bound Rab protein is measured directly (Frasa et al., 2012), whereas pull-down assays are performed by using its specific effector protein to collect active Rab protein from lysates of cells with or without expression of GAP proteins (Itoh and Fukuda, 2006). These assays sometimes yield different results. For example, RUTBC1 has been reported to show strong


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in vitro GAP activity toward Rab32 and Rab33B, but only weak activity toward Rab38, the closest homologue of Rab32 having a redundant function in melanocytes (Nottingham et al., 2011), whereas RUTBC1 has been shown to inactivate both Rab32 and Rab38 in pull-down assays (Marubashi et al., 2016). In addition, in vitro GAP assays in different studies have often identified different substrates of Rab-GAPs (summarized in Fukuda, 2011 and Frasa et al., 2012). Moreover, all TBC1D10 family proteins show GAP activity toward Ras (Nagai et al., 2013). Consequently, it will be necessary to check the consistency of the results of GAP assays performed by different methods and to analyze other phenotypes induced by gene manipulations in the future. Using C. elegans and D. melanogaster Rab-GAP (or Rab) mutants or a recently developed genome editing technique, CRISPR/Cas9, in mammalian cells will be effective to resolve previous conflicting results. Since autophagy is induced by stresses, including starvation, certain signaling cascades are required to activate autophagy, and since the activity of autophagic Rabs must be regulated by such signals, future investigation of Rab-GAPs (and also Rab-GEFs) may lead to the discovery of an unknown signaling pathway(s) that regulates autophagy. One candidate that mediates such a signaling pathway is phosphorylation of Rab-GAPs, because the nutrient signal is transmitted mainly through the mTORC1 kinase complex and regulates starvation-induced autophagy (Bar-Peled and Sabatini, 2014; Shimobayashi and Hall, 2016). Another candidate is ubiquitination, because TBC1D15 is ubiquitinated by Parkin (Sarraf et al., 2013). Parkin is tethered on mitochondria by PINK1, which is stably localized only at depolarized mitochondrial surfaces where it induces clearance of damaged mitochondria (Pickrell and Youle, 2015). Since TBC1D15 and TBC1D17 are constitutively localized at mitochondria, it is tempting to speculate that TBC1D15 (and TBC1D17) activity is regulated by ubiquitination. To date, however, there have been no reports of autophagy-related RabGAPs being regulated by posttranslational modifications (e.g., phosphorylation) other than ubiquitination. Searching for such modifications would be an exciting approach to revealing the regulatory mechanism of Rab-GAPs in the future. The field of Rab/Rab-GAP research in autophagy has only just begun. We are confident that future advances in this field will resolve some of the discrepancies between the results of previous studies and determine the precise mechanism of Rab-mediated autophagosome formation and maturation.

Acknowledgments This work was supported in part by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan (grant numbers 25440077 to T.I. and 24370077 and 26111501 to M.F.) and by a grant from the Takeda Science Foundation (to M.F.).

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C H A P T E R

7 The Role of Histone Deacetylase Inhibition in the Accumulation and Stability of Disease-Related Proteins Elizabeth A. Thomas O U T L I N E Introduction 160 Histones and HDAC Enzymes 160 Class I HDACs 161 Class II HDACs 162 Class III and IV HDACs 163 HDAC Inhibitors 163 Cancer Versus Neurodegenerative Disorders 165 Ubiquitin Proteasomal and Autophagy Pathways 166 Protein Folding Disorders/Proteopathies 167 Huntington’s Disease 167 Alzheimer’s Disease 168 Parkinson’s Disease 168

A Role for HDAC Inhibitors in Proteopathies 169 HDAC Inhibitors and HD 169

Autophagy and Htt clearance 170 Altered Ubiquitination-Related Gene Expression in Response to HDAC Inhibitors 171

HDAC Inhibitors in AD HDAC Inhibitors and PD Models Conclusions/Future Perspectives

173 174

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Abstract

Novel treatment strategies for neurodegenerative disorders have included histone deacetylase (HDAC) inhibitors. These compounds typically act by increasing acetylation of histone proteins, leading to a relaxed chromatin state and facilitation of gene expression. However, their effects on nonhistone substrates are becoming clearer, which may also contribute to their mechanisms of action. Accumulation and aggregation

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7. THE ROLE OF HISTONE DEACETYLASE INHIBITION ON DISEASE PROTEINS

of disease-causing proteins is a hallmark of several neurodegenerative disorders such as Parkinson’s, Alzheimer’s, and Huntington’s diseases. Treatment options that effectively prevent the development of misfolded and aggregated proteins in these disorders would represent an important disease-modifying therapeutic candidate. This chapter summarizes studies that have demonstrated a role of HDAC inhibitors in modulation of the expression and aggregation of several disease proteins, including huntingtin, betaamyloid, and alpha-synuclein.

INTRODUCTION Studies over the past 10 years have implicated histone deacetylase (HDAC) inhibitors as a therapeutic option for several neurodegenerative diseases. A common characteristic of these diseases is aberrant transcriptional regulation because of the disrupted function of histone-modifying complexes and altered chromatin-related factors. These effects have provided the initial rationale for the use of HDAC inhibitors as a treatment option. However the exact mechanism(s) by which HDAC inhibition can improve disease phenotypes in these neurological disorders remains unclear. In addition to restoring transcriptional balance to disease or disease-modifying genes, HDAC inhibitors have been shown to affect protein clearance pathways, including the ubiquitin proteasomal and autophagy pathways. Aggregation and accumulation of disease-causing proteins is a hallmark of several prominent neurodegenerative disorders. This review summarizes potential roles of HDAC inhibition to affect the accumulation and/or clearance of disease proteins, including those associated with Huntington’s disease (HD), Parkinson’s disease (PD), and Alzheimer’s disease (AD).

HISTONES AND HDAC ENZYMES Histone proteins play structural and functional roles in all nuclear processes. The aminoterminal tails of these histones contain amino acid residues that are sites for acetylation, methylation, phosphorylation, and ubiquitination. One of the most widely studied histone posttranslational modifications is acetylation, which is the transfer of an acetyl group from acetyl coenzyme A to a lysine residue in the acceptor histone. Histone acetylation was first described in 1964 (Allfrey et al., 1964), and is a highly dynamic process which is modulated by the actions of two opposing enzymes, histone acetyltransferases (HATs) and HDACs (Kornberg and Lorch, 1999; Strahl and Allis, 2000). The correlation between histone acetylation and increased transcription has been known for many years, whereby increases in HAT activity promote acetylation of histone proteins leading to increased gene transcription by creating a more open conformation of chromatin. In contrast, HDAC activity involves removing the acetyl group from histones, which results in a decrease in the space between the nucleosome and the DNA that is wrapped around leading to gene repression. However, in more recent years, HATs and HDACs have been shown to modify a number of nonhistone proteins (Glozak et al., 2005). The increasing number of acetylated nonhistone proteins suggests an important role of HDACs in the regulation of cellular processes beyond chromatin and gene transcription


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(Glozak et al., 2005). One of the emerging concepts is that the acetylation status of many proteins regulates their stability. Increased acetylation of proteins can promote enhanced degradation via autophagy. However, lysine residues can also be targets for ubiquitination, a tag for proteasomal degradation. Deacetylation of these nonhistone proteins by HDACs opens yet another exciting new field of discovery in the role of the dynamic acetylation and deacetylation on cellular function. HATs makes up a diverse family of proteins, including Gcn5-related N-acetyltransferase superfamily members, MYST proteins, global coactivators p300 and CREB-binding protein (CBP), nuclear receptor coactivators, TATA-binding protein-associated factor TAF(II)250 and its homologs, and subunits of RNA polymerase III general factor TFIIIC (An, 2007). A review of the HAT enzymes has been published previously (An, 2007) and will not be summarized here. In contrast, HDAC enzymes represent a related family of proteins with structural similarities (Gregoretti et al., 2004). In humans the HDAC family of enzymes has 18 subtypes (Xu et al., 2007). HDACs exist in large multiprotein complexes, and evidence suggests that most, if not all, HDAC enzymes require interaction with other HDACs or proteins for optimal function (Adcock et al., 2006; Hildmann et al., 2007). HDACs lack a DNA-binding motif and one function of HDAC-interacting proteins is recruitment to their chromatin targets (Reichert et al., 2012). HDAC-containing repressor complexes consist of a multitude of components that have cell-type, stage-specific expression. An overview of the HDAC family is depicted in Table 7.1.

Class I HDACs The class I family of HDACs include HDACs 1, 2, 3, and 8, all of which are widely expressed in the brain (Broide et al., 2007; Thomas, 2009). HDACs 1 and 2 are strictly observed in the nucleus, where HDACs 3 and 8 can shuttle between the nucleus and the cytoplasm and deacetylate substrates in either compartment. Class I HDACs interact with key proteins as part of large multiunit complexes. HDAC1 can interact with several other HDAC proteins, but most notably, it functions in combination with HDAC2 in several repressor complexes. HDAC1 and HDAC2 form a heterodimer, which constitutes the catalytic core of the Sin3a, NuRD, and REST/CoREST complexes. The Sin3 and the NuRD complexes are broadly acting modulators of gene transcription (Reichert et al., 2012), whereby the REST/CoREST complex has more specific functions in the transcriptional repression of neural genes (Andrés et al., 1999). HDAC3 shares structural and functional features with other class I HDACs, but it exists in multisubunit complexes that are different from other known HDAC complexes (Thomas, 2014). HDAC3 is most commonly found in transcription corepressor complexes containing the nuclear receptor corepressor (NCoR) and silencing mediator for retinoid and thyroid receptors (SMRTs), which regulates transcriptional repression of a wide range of genes (Wen et al., 2000). Although HDAC3 is the primary HDAC enzyme in NCoR/SMRT complexes, other HDACs can be recruited in a transcription factor- or context-specific manner (Huang et al., 2000; Fischle et al., 2001, 2002). In particular, class II HDACs (4, 5, 7, and 10) have been shown to interact with HDAC3 in NCoR/SMRT complexes (Huang et al., 2000; Fischle et al., 2001, 2002). Specifically, HDAC4 has been found to coimmunoprecipitate


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TABLE 7.1 The HDAC Superfamily of Enzymes Class

Member

Chromosomal Position

Cofactor

Length (Amino Acids)

Subcellular Localization

I

HDAC1

1p34.1

Zn2+

482

Nuclear

HDAC2

6q21

Zn2+

488

Nuclear

2+

428

Nuclear/cytoplasmic

2+

377

Nuclear/cytoplasmic

2+

1084

Nuclear/cytoplasmic

2+

1122

Nuclear/cytoplasmic

2+

952

Nuclear/cytoplasmic

2+

HDAC3 HDAC8 IIa

HDAC4 HDAC5 HDAC7

IIb

III

Xq13 2q37.2 7q21 12q13.1

Zn Zn Zn Zn Zn

HDAC9a

7p12.1

Zn

1011

Nuclear/cytoplasmic

HDAC9b

7p12.1

Zn2+

879

Nuclear/cytoplasmic

HDAC6

Xp11

Zn2+

1215

Cytoplasmic

HDAC10

22q13.3

Zn2+

669

Cytoplasmic

SIRT1

10q21.3

NAD+

747

Nuclear

+

389

Cytoplasmic

+

399

Mitochondria

+

314

Mitochondria

+

310

Mitochondria

+

355

Nuclear

+

400

Nuclear

347

Nuclear/cytoplasmic

SIRT2 SIRT3 SIRT4 SIRT5 SIRT6 SIRT7 IV

5q31.3

HDAC11

19q13 11p15.5 12q 6p23 19p13.3 17q25 3p25.2

NAD NAD NAD NAD NAD NAD 2+

Zn

HDAC, histone deacetylase; NAD, nicotinamide adenine dinucleotide.

with HDAC3 via its C-terminal domain and disruption of this interaction resulted in loss of observed HDAC activity. Importantly, it has been indicated that the HDAC domains of HDACs 4 and 5 do not possess intrinsic enzymatic activity as isolated polypeptides but are associated with HDAC activity only by interacting with HDAC3, via the transcriptional corepressor NCoR/SMRT complex (Huang et al., 2000; Fischle et al., 2001, 2002).

Class II HDACs The class II family of HDACs can be further divided based on structural parameters into two subclasses: class IIa includes HDACs 4, 5, 7, and 9, whereas class IIb includes HDACs 6 and 10 (Xu et al., 2007) (Table 7.1). Class II enzymes share significant sequence and structural homology and, like class I HDACs, require zinc for catalytic activity. The other class II


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163

HDACs shuttle between the nucleus and the cytosol. Members of both subclasses display tissue- and cell-specific expression, but importantly they are all expressed at moderately high levels in the brain (Broide et al., 2007; Thomas, 2009). HDAC6 has been implicated more directly in the process of autophagy by regulating key players, hence warrants special mention for this review. HDAC6 is present predominantly in the cytosol catalyzing the deacetylation of substrates other than histone proteins, including alpha-tubulin, the chaperone heat shock protein 90 (HSP90), the actin-binding protein cortactin, and β-catenin (Zhang et al., 2007; Kekatpure et al., 2009). Research in the last decade has revealed that HDAC6 is a major component of the aggresome-autophagy pathway (Yan, 2014). HDAC6 contains a C-terminal zinc finger ubiquitin-binding domain, allowing interactions with polyubiquitin chains. This feature allows the retrograde transport of ubiquitinated proteins along the microtubules. The role of HDAC6 in neurodegeneration has been at least partially elucidated so far, although the strategy for developing promising therapeutics targeting HDAC6 is still controversial. Specific HDAC6 inhibitors can exert neuroprotection by increasing the acetylation levels of α-tubulin with subsequent improvement of the axonal transport, which is often impaired in neurodegenerative disorders. On the other hand an induction of HDAC6 could theoretically contribute to the degradation of protein aggregates, such as those associated with various neurodegenerative disorders, including AD, PD, and HD. This topic has been the subject of excellent reviews (Simoes-Pires et al., 2013; Yan, 2014), hence will not be covered here.

Class III and IV HDACs The class III NAD+-dependent HDACs, called sirtuins because of their homology to the yeast ortholog silent information regulator 2 (SIR2), comprise seven mammalian members (Blander and Guarente, 2004). SIRTs 1, 2, 6, and 7 are found in both the cytoplasm and nucleus, while SIRTs 3, 4, and 5 are found localized to the mitochondria (Table 7.1). Class IV is represented by a single member, HDAC11 (Gao et al., 2002), which shares similar characteristics to HDACs in the class I and II families. Mainly found in the nucleus, HDAC11 has few known substrates, but is abundantly expressed in the brain (Broide et al., 2007).

HDAC INHIBITORS A wide variety of inhibitors have been developed that can inhibit the zinc-dependent classes of HDACs; these fall into four main classes according to their chemical structure: (1) the small carboxylates, such as sodium butyrate, valproic acid, and sodium phenylbutyrate; (2) the hydroxamic acids, such as trichostatin A (TSA), suberoylanilide hydroxamic acid (SAHA), and their derivatives; (3) the benzamides, such as MS-275; and (4) the cyclic peptides, including apicidin and depsipeptide (Drummond et al., 2005) (see Table 7.2). It is important to note that these small-molecule HDACs do not affect class III HDACs, the sirtuins, due to the structural and functional dissimilarity between these enzymes and classes I, II, and IV enzymes.


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TABLE 7.2 Summmary of Studies Showing the Effects of HDAC Inhibitors on Disease Proteins Disease

Disease Protein Inhibitor

Model

Findings

References

Reduced Htt aggregates in cortex

Jia et al. (2012)

Huntington’s Huntingtin disease

HDACi 4b

N171-82Q transgenic mice


HDACi 4b

WT and N171-82Q Increased transgenic mice phosphorylated/ acetylated Htt

Jia et al. (2012)


HDACi 874


Reduced Htt aggregates in cortex

Jia et al. (2012)


Suberoylanilide R6/2 transgenic hydroxamic acid mice

Reduced insoluble Htt aggregate load in cortex and brain stem; no effect in hippocampus

Mielcarek et al. (2011)


T247, T326, T130 Hela cells

Decreased soluble cytoplasmic Htt; Increased insoluble nuclear Htt

Mano et al. (2014)


Phenylbutyrate

No effect on Htt aggregates in striatum

Gardian et al. (2005)

Alzheimer’s disease

Amyloid beta

GammaTg2576 transgenic hydroxybutyrate mice

Reduced amyloid beta levels in brain

Klein et al. (2015)


Amyloid beta

Phenylbutyrate

Tg2576 transgenic mice

Decreased amyloid plaque deposition

Ricobaraza et al. (2011)


Amyloid beta

Ms-275

APP/PS1 transgenic mice

Decreased amyloid plaque deposition in hippocampus and cortex

Zhang and Schluesener (2013)


Amyloid beta

Trichostatin A

APP/PS1 transgenic mice

No effect on amyloid load in hippocampus or cortex

Yang et al. (2014)


Amyloid beta

Class II inhibitors

3xtg transgenic mice

Reduced APP cleavage products

Sung et al. (2013)

Parkinson’s disease

α-Synuclein

Phenylbutyrate

Alpha-synuclein transgenic mice

Reduced alphasynuclein aggregation

Zhou et al. (2011)


α-Synuclein

Phenylbutyrate

Alpha-synuclein transgenic mice

Lower levels of phosphorylated α-synuclein

Ono et al. (2009)


α-Synuclein

BetaTDP-43 transgenic Decreased α-synucleinhydroxybutyrate worms GFP aggregation

Edwards et al. (2014)


α-Synuclein

Valproic acid

Leng and Chuang (2006)


WT rat cerebellar granule cells

Increased expression of WT α-synuclein


HDAC Inhibitors

165

Pan-specific inhibitors include the widely used inhibitors, SAHA and TSA; however, their potencies at inhibiting class II HDACs are much lower compared to their effects on class I enzymes. TSA is the most potent inhibitor with effective concentrations in the single-digit nanomolar range (Khan et al., 2008). VPA, although much lower in potency, exhibits specificity for class I enzymes. Other compounds show some isotype selectivity with MS-275, preferentially inhibiting HDAC1 and demonstrating no activity at class II HDACs, while apicidin shows selectivity toward HDACs 2 and 3 (Khan et al., 2008). The reported potencies of common HDAC inhibitors against different HDAC substrates vary considerably in vitro. This apparent discrepancy is largely due to differences in the sources of the enzymes (natural vs recombinant), substrates used in the assays, and assay conditions. A further caveat is that not all HDAC isoforms have been tested with the reported inhibitors. In recent years, many reports describing novel isoform-selective HDAC inhibitors have been published (Bieliauskas and Pflum, 2008; Chou et al., 2008). Attempts to improve selectivity have focused on modifying the capping group, linker region, and metal-binding moieties of pan-specific inhibitors, such as TSA and SAHA. In addition a family of pimelic diphenylamide HDAC inhibitors of the benzamide type have been generated (Herman et al., 2006). These compounds show class I specificity, demonstrating no activity against class II HDACs, with several members of this class showing selectivity for the HDAC3 isoform over HDAC1 (i.e., HDACs 4b, 106, 966), with lower activity at HDACs 2 and 8 (Chou et al., 2008).

Cancer Versus Neurodegenerative Disorders HDAC inhibitors are most commonly therapeutically used as anticancer agents, where they have been shown to cause growth arrest, differentiation, and/or apoptosis of tumor cells by altering the transcription of a small number of genes (Marks et al., 2001). Accordingly, clinical trials are ongoing for the use of HDAC inhibitors in various cancers: nonsmall cell cancers and hepatocellular carcinomas, leukemia and T-cell lymphoma, among others. However, data emerging over the past 10 years have identified HDAC inhibitors as candidate drugs for the treatment of neuropsychiatric and neurodegenerative disorders. Initial findings demonstrated beneficial properties of these classical compounds in cell culture models; however, in vivo studies in mice have provided the best insight regarding the potential therapeutic effects of HDAC inhibitors in neurodegenerative disorders, whereby several different types of compounds have shown preclinical efficacy in animal models (see reviews: Butler and Bates, 2006; Morrison et al., 2007; Abel and Zukin, 2008; Hahnen et al., 2008; Marsh et al., 2008). It seems counterintuitive that a drug class studied for cancer therapy, where cells resist dying, could be efficacious for neurodegenerative diseases, which are associated with cell death. However a number of cell systems have emerged in recent years, which represent a substantial pathological convergence between cancer and neurodegenerative disorders (Devine et al., 2011). For example, alterations in protein folding and degeneration, cell cycle and DNA repair, mitochondria and oxidative stress, and chronic inflammation are all implicated in both cancer and neurodegeneration (Devine et al., 2011).


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Although the behavioral improvements seen in response to HDAC inhibitors in mouse models are striking, the exact mechanisms of action by which HDAC inhibition can improve disease phenotypes in these neurological disorders remain elusive, and may diverge substantially from the mechanisms by which they are useful to treat cancer. Possibilities include restoring transcriptional balance to disease or disease-modifying genes, activating neuroprotective mechanisms, or affecting protein clearance pathways, including the ubiquitin proteasomal and autophagy pathways, which will be discussed below.

UBIQUITIN PROTEASOMAL AND AUTOPHAGY PATHWAYS The two major protein degradation systems in the brain are the ubiquitin-proteasome system (UPS) and autophagy. The first, UPS, targets single proteins for degradation by tagging them with ubiquitin (Glickman and Ciechanover, 2002). Ubiquitin is a highly conserved protein with 76 amino acids. Substrate proteins can be tagged by different ubiquitin modifications, including mono- and polyubiquitylations. This tagging process leads to their recognition by the 26S proteasome, a large multicatalytic protease complex that degrades ubiquitinated proteins to small peptides (Baumeister et al., 1998). This process occurs via the sequential action of three enzyme groups: the ubiquitin-activating enzymes (E1), ubiquitinconjugating enzymes (E2), and substrate-specific ubiquitin ligases (E3), which catalyze the transfer of activated ubiquitin to targeted proteins. It is now known that the E1, E2, and E3 gene groups consist of more than hundreds of members, although the exact function of the individual subtypes is not clear. The other major protein degradation pathway is the autophagy-lysosomal pathway, which generally removes damaged or aggregated long-lived proteins or organelles (Levine and Kroemer, 2008). There are three types of autophagy: macroautophagy, microautophagy, and chaperone-dependent autophagy. Here, we will refer mainly to macroautophagy, the autophagy type that requires sequestration of substrates in a doublemembrane vesicle, called the autophagosome, which then fuses with the lysosome resulting in degradation via the activity of lysosomal hydrolases. This process is controlled by highly conserved autophagy (ATG) genes. Core Atg proteins, including beclin, Atg7, and microtubule-associated protein light chain 3 protein (Map1lc3a), are essential for the formation of autophagosomes (Levine and Kroemer, 2008). Beclin is involved in the initial autophagosome formation through a phosphatidylinositol 3-OH kinase complex, whereas Atg 7 and Map1lc3a are involved in autophagic vesicle elongation through a ubiquitin-like conjugation pathway (Levine and Kroemer, 2008). The importance of basal autophagic activity in neurons has been demonstrated in neuron-specific Atg7- or Atg5-knockout mice, which develop ubiquitinated protein inclusions and neurodegeneration (Hara et al., 2006; Komatsu et al., 2006). The collaboration between the UPS and autophagy appears to be essential to protein quality control in the cell. UPS proteolytic function often becomes inadequate in proteinopathies leading to activation of autophagy, which acts to remove abnormal proteins especially the aggregated forms. The link between HDAC function and these two clearance pathways is especially important for protein folding disorders.


Protein Folding Disorders/Proteopathies

167

PROTEIN FOLDING DISORDERS/PROTEOPATHIES Accumulation and aggregation of disease-causing proteins is a hallmark of several neurodegenerative disorders, called proteopathies, and include disease such as PD, AD, and HD, which will be discussed in this chapter. Briefly, HD is associated with polyglutamineexpanded huntingtin (Htt) aggregates, which accumulate in both the nucleus and cytoplasm (Ross and Tabrizi, 2011). In AD the hydrophobic peptide beta-amyloid is produced in cells but accumulates in extracellular plaques (LaFerla et al., 2007). Finally, in PD, cytoplasmic Lewy bodies are protein aggregates mainly comprise the protein, α-synuclein (Uversky, 2007). These misfolded and aggregated proteins are cleared by one or both of two protein degradation pathways described above; hence drugs targeting these protein degradation systems have gained attention as therapeutic options. Each of these proteopathies is discussed further, along with evidence implicating a role of HDAC inhibitors in altering the clearance and stability of the corresponding disease proteins.

Huntington’s Disease HD is an inherited, progressive autosomal-dominant neurodegenerative disorder characterized by motor, psychiatric, and cognitive decline that affects one person per 10,000 people. Prominent neuronal loss occurs not only in the striatum but also in cortical regions. HD is caused by a CAG repeat expansion in the 5′ coding region of the Huntington (HTT) gene (Group, 1993). A CAG repeat number of 40 leads to the development of HD, while lengths below 35 repeats are generally considered nonpathological; 36–39 repeats show incomplete penetrance (Myers et al., 1993; Kremer et al., 1994). Within the expanded range, longer repeats cause earlier onset. The mutant HTT gene encodes the protein Htt, containing an expanded polyglutamine tract, which leads to the formation of insoluble aggregates in the brain. Such aggregates represent a hallmark feature of the disease in humans as well as in animal models of the disease. Significant evidence suggests that levels of mutant Htt strongly correlate with severity of HD phenotypes. Hence, one therapeutic approach in HD is to improve the degradation of accumulated mutant proteins. Studies have implicated important roles for both the UPS and autophagy in the clearance pathway for mutant Htt fragments (Ravikumar et al., 2004; Yamamoto et al., 2006). Htt can undergo posttranslation modifications, such as ubiquitination, SUMOylation, phosphorylation, and acetylation, at several amino acid residues, and this likely contributes to its clearance and stability. Initial studies found that mutant Htt aggregates could be labeled with antibodies to ubiquitin. It is now known that Htt protein can be ubiquitinated at several residues signaling degradation by the proteasome. Furthermore, dysfunction in the UPS has been implicated in HD, which suggests that UPS cannot handle the misfolded Htt overload, hence, may lead to their accumulation. The same ubiquitinated lysine residues are also targets of SUMOylation (Steffan et al., 2004), a covalent protein modification with small ubiquitin-like modifiers (SUMO), which may have the opposite effect as ubiquitin. In cultured cells SUMOylation was found to stabilize mutant Htt, reduce its ability to form aggregates, and promote its capacity to repress transcription (Steffan et al., 2004).


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Importantly, Htt can be acetylated. In particular, increased acetylation at lysine 444 of the Htt protein has been shown to facilitate trafficking of mutant Htt into autophagosomes (Jeong et al., 2009). This action subsequently improved Htt clearance reversing the toxic effects of this protein in primary striatal and cortical neurons, as well as in a transgenic C. elegans HD model (Jeong et al., 2009). These data suggest that selective clearance of the mutant Htt protein can be achieved by hyperacetylation of the mutant protein with HDAC inhibitors, although this was not specifically studied.

Alzheimer’s Disease AD is a neurodegenerative disorder that currently affects nearly 2% of the general population, with the risk dramatically increasing in individuals beyond the age of 70 years. Since life expectancies are increasing, it is estimated that the number of individuals afflicted with AD will double in the next 10–15 years, causing a huge economical burden to our societies. Symptoms of AD include progressive loss of memory, task performance, speech, and recognition of people and objects. There is degeneration of neurons particularly in the basal forebrain and hippocampus. Hallmark neuropathological features of AD include extracellular plaques and intracellular tangles (Mattson, 2004; Goedert, 2015). AD involves two major kinds of protein aggregates. Extracellular aggregates known as neuritic plaques contain the amyloid beta peptide, which is derived from proteolytic cleavage of the amyloid precursor protein (APP), upon cleavage by beta and gamma secretase. Amyloid beta molecules can aggregate to form flexible soluble oligomers, which may exist in several forms, or in aggregated amyloid plaques. There are also intracellular aggregates of the microtubule-associated protein tau called neurofibrillary tangles. Genetic mutations have been identified that are responsible for rare familial forms of the disease. These individual mutations can appear in the APP gene, as well as in the presenilins, which are involved with the cleavage of the APP protein (Ross and Poirier, 2004). About 2–5% of all AD patients suffer from familial AD that is characterized by an early onset. In contrast, the more common form of AD is the so-called late onset, or sporadic AD, that affects 95–98% of all AD patients. Evidence implicates deregulated amyloid beta homeostasis as an early event in AD pathology (Masters et al., 1985), and, indeed, all familial and sporadic forms of AD lead to increased production of this peptide. For this reason, most AD therapeutics have targeted the amyloid beta peptide, although tau-targeted therapies are also being pursued (Barten and Albright, 2008).

Parkinson’s Disease PD is a progressive neurodegenerative disorder that affects 1% of the population over the age of 65 years (Gasser, 2001). Approximately six million people worldwide have PD. This disease is characterized by resting tremor, rigidity, slow movements, and other features such as postural and autonomic instability. It is caused by degeneration of dopaminergic neurons in the substantia nigra of the midbrain. The discovery of several genes in which mutations cause early-onset forms of PD has greatly accelerated research progress. Mutations in the alpha-synuclein gene cause autosomal-dominant PD via a gain-of-function mechanism. In contrast, recessive early-onset PD can be caused by mutations in the genes


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169

encoding parkin, DJ-1, or PINK1 (Dawson and Dawson, 2003; Valente et al., 2004), presumably by a loss-of-function mechanism. The pathological hallmark of adult-onset PD is the Lewy body, an inclusion body found in the cytoplasm of neurons, often near the nucleus. Lewy bodies are most striking in the substantial nigra, but can also be present in cerebral cortical and other neurons. There are also aggregates in neurites, which are referred to as Lewy neurites. A major constituent of Lewy bodies is aggregated alpha-synuclein protein. Lewy bodies can also be labeled for ubiquitin, suggesting its degradation by the UPS. It is therefore not surprising that mutations in components of this machinery can cause familial PD, and altered proteasomal function is observed in sporadic PD (Devine et al., 2011). To date, no treatment has been identified that halts the death of dopaminergic neurons that underlies PD, but many therapeutic efforts have focused on reducing the presence of aggregated alpha-synuclein.

A ROLE FOR HDAC INHIBITORS IN PROTEOPATHIES An accumulating body of literature has demonstrated preclinical efficacy of HDAC inhibitors in many different disease models for HD, AD, and PD. In some cases the beneficial behavioral effects of HDAC inhibitors were associated with increase histone acetylation and gene expression changes, while in other studies these compounds were found to alter posttranslational modifications of nonhistone proteins. Below, I have summarized studies that have described changes in the levels of the relevant disease-causing proteins in response to treatment with HDAC inhibitors.

HDAC Inhibitors and HD HD was the first neurodegenerative disorder in which the possibility that HDAC inhibitor therapy might slow or prevent the progressive neurodegeneration was considered. A common characteristic of HD, as well as other polyglutamine diseases, is aberrant transcriptional regulation, due to the disrupted function of histone-modifying complexes and altered interactions of the polyglutamine-expanded Htt protein with chromatin-related factors. In particular, several studies have provided evidence that the chromatin acetylation status is greatly impaired in HD, with a common mechanism being the loss of function of a specific HAT: the CBP. These features have been reviewed previously (Butler and Bates, 2006; SadriVakili and Cha, 2006; Hahnen et al., 2008) and have provided the rationale for the proposed use of HDAC inhibitors as a relevant treatment approach for HD. While initial efficacy studies were carried out in cell and fly models, many studies over the past 10 years have demonstrated beneficial effects on disease behaviors of SAHA (Hockly et al., 2003), sodium butyrate (Ferrante et al., 2003), phenylbutyrate (Gardian et al., 2005) HDACi 4b (Thomas et al., 2008; Jia et al., 2012, 2016) in HD mouse models. With the more recent identification of many nonhistone substrates for HDAC enzymes, the potential pathways targeted by HDAC inhibitors have greatly expanded beyond chromatin-mediated effects. There are several mechanisms by which HDAC inhibitors can be acting to improve disease phenotypes in HD. Fig. 7.1 highlights potential mechanisms of such compounds to clear Htt aggregation, which will be discussed below.


170


HDAC inhibitor

(–)

(–) HDAC1

HDAC3

Ac

Ac

Ac

Histone protein

Ac

mHtt Ac

Autophagic degradation of mHtt

Increased histone acetylation and gene expression changes

UPS-related genes Ub

mHtt

Proteasomal degradation of mHtt

Reduced mHtt aggregates FIGURE 7.1 Potential chromatin- and nonchromatin-related mechanisms for how HDAC inhibitors can lower Htt aggregates in Huntington’s disease. Inhibition of HDAC1 and HDAC3 enzymes can lead to lowered mHtt levels. Inhibition of HDAC1 can lead to increased acetylation of mHtt protein and degradation by autophagy. Alternatively, inhibiting HDACs 1/3 enzymes can increase histone acetylation and the expression of genes related to the UPS, which could then promote ubiquitination of mHtt protein and subsequent clearance by the UPS. Ac, Acetyl group; HDAC, histone deacetylase; mHtt, mutant huntingtin; UPS, ubiquitin proteasomal system.

Autophagy and Htt clearance Acetylation of lysine 444 of the Htt protein is an important modification that was found to be regulated by the opposing activities of CBP and HDAC1 (Jeong et al., 2009). Specifically overexpression of HDAC1 decreased acetylation of mutant Htt and knockdown of endogenous HDAC1 by shRNA significantly increased acetylation of mutant Htt at lysine 444 in cultured primary striatal and cortical neurons (Jeong et al., 2009). Increased acetylation of Htt was associated with improved trafficking of mutant Htt into autophagosomes, improved clearance of the mutant protein by macroautophagy, and also reversed the toxic effects of mutant Htt in primary striatal and cortical neurons and in a transgenic C. elegans



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model of HD (Jeong et al., 2009). These findings were supported by a separate group of researchers who demonstrated that downregulation of HDAC1 is essential for the degradation of mutant Htt through lithium-induced autophagic pathway (Wu et al., 2013). These data suggest that selective clearance of the mutant Htt protein could feasibly be achieved by treating with HDAC inhibitors. Phosphorylation is also known to regulate protein degradation, alter subcellular localization of proteins, and lead to changes in other protein modifications such as ubiquitination, SUMOylation, and acetylation. Phosphorylation of Htt at serine 16 and threonine 3 was found to be elevated in response to HDACi 4b treatment in N171-82Q transgenic mice, which express an N-terminal fragment of human Htt with 82 glutamines (Jia et al., 2012) (Table 7.2). Phosphorylation of S13/S16 has been shown to specifically promote acetylation of Htt at K9 (Thompson et al., 2009), a form of Htt that coexists with phosphorylation of S13/S16. Further results found a significant increase in AcK9/pS13/pS16 immunoreactivity in cortical samples from HDACi 4b-treated WT and N171-82Q transgenic mice (Jia et al., 2012). Phosphorylation and acetylation of Htt at these residues have been linked to autophagic clearance of Htt by the lysosome (Thompson et al., 2009); hence, these findings suggest that HDACi 4b may be acting, in part, to alter clearance of Htt by the lysosomal pathway. The exact role of how modified WT Htt protein can affect the mutant protein and subsequent effects on pathology, however, are unclear. Furthermore, IkB kinase (IKK) activation has been shown to induce phosphorylation and acetylation of the Htt protein, leading to its clearance by the proteasome and lysosome (Thompson et al., 2009). We found that HDACi 4b treatment significantly increased the expression of several IKK gene family members, suggesting that it may be acting on autophagic processes. In addition, HDACi 4b was found to increase the expression of the autophagy-related 4C (ATG4c) gene in mouse cortex (Jia et al., 2012), providing additional support for this notion. These findings are consistent with previous studies showing that SAHA can activate autophagy by a mechanism involving increased expression of the autophagic factor LC3 and inhibition of the nutrient-sensing kinase mammalian target of rapamycin (Gammoh et al., 2012). Altered Ubiquitination-Related Gene Expression in Response to HDAC Inhibitors Because HDAC inhibitors are primarily thought to act by altering gene expression, several studies have used microarray analysis in attempts to identify those genes altered by drug treatment. An early study by Gardian and colleagues investigated the effects of phenylbutyrate treatment in N171-82Q transgenic HD mice on global gene expression using Affymetrix gene arrays (Gardian et al., 2005). Several UPS-related gene expression changes were found, including increased expression of ubiquitin-specific protease 29 (Ups29), Proteasome subunit, α type 3 (Psma3), Proteasome 26S subunit, ATPase 3 (Psmc3), and decreased expression of another related gene, Proteasome 26S subunit, non-ATPase, 10 (Psmd10) (Gardian et al., 2005) (see Table 7.3). Despite these changes, no differences in Htt aggregates in the striatum were detected using immunohistochemistry, although effects on aggregates in other brain regions were not reported (Gardian et al., 2005) (Table 7.2). A later study by Jia and colleagues also found increased expression of UPS-related genes in response to an HDAC1/3-selective inhibitor, HDACi 4b, using microarray analysis in different regions from R6/2 transgenic mice, which express exon 1 of the human HTT gene and


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TABLE 7.3 Ubiquitin-Related Genes Altered in Expression by HDAC Inhibitors in Mouse Models Gene ID

Gene Name

Drug

Dose

Effect Model

Pml

Promyelocytic leukemia

HDACi 4b

50 mg/kg

↑

Psma3

Proteasome subunit, α type 3

Psmc3

Proteasome 26 S subunit, ATPase 3

Psmd10 Proteasome 26 S subunit, non-ATPase, 10

References

R6/2/N171-82Q Tg mice

Jia et al. (2012)

Phenylbutyrate 100 mg/kg ↑

N171-82Q Tg mice



N171-82Q Tg mice


Phenylbutyrate 100 mg/kg ↓

N171-82Q Tg mice


Sumo2

SMT3 suppressor of mif two 3 homolog 2

HDACi 4b

50 mg/kg

↓


Jia et al. (2012)

Uba7

Ubiquitin-like modifier activating enzyme 7

HDACi 4b

50 mg/kg

↓


Jia et al. (2012)

Ube2e3 Ubiquitin-conjugating HDACi 4b enzyme E2E 3

50 mg/kg

↑


Jia et al. (2012)

Ubiquitin-conjugating HDACi 4b enzyme E2K

50 mg/kg

↑


Jia et al. (2012)

HDACi 4b

50 mg/kg

↑


Jia et al. (2012)

Ube2K

Ubqln2 Ubiquilin 2 Usp18

Ubiquitin-specific peptidase 18

HDACi 4b

50 mg/kg

↑


Jia et al. (2012)

Usp28


HDACi 4b

50 mg/kg

↑


Jia et al. (2012)

Usp29

Ubiquitin-specific protease 29


N171-82Q Tg mice


Usp3


TSA

C57Bl/6

Vadnal et al. (2012)

7.5 mg/kg

↑

150 CAG repeats, and these expression differences were validated in a second HD mouse model, the N171-82Q transgenic mouse line (Jia et al., 2012). In the cortex HDACi 4b was found to normalize Htt-induced deficits in the expression of ubiquitin-conjugating enzyme E2K (Ube2k), ubiquitin-conjugating enzyme E2E 3 (Ube2e3), ubiquitin-specific peptidase 28 (Usp28), at 3 days and 6 weeks of treatment but not at the late stages of disease. In the striatum HDACi 4b caused significant increases in the expression of Ubiquilin 2 (Ubqln2), promyelocytic leukemia (Pml), and Usp28 in N171-82Q transgenic mice after 12 weeks of treatment (Jia et al., 2012) These results are summarized in Table 7.3. Increased expression of any of these genes might be expected to increase in the ubiquitination of Htt protein,



173

thereby promoting its clearance by the proteasome, as has been suggested previously (Kalchman et al., 1996; Jana et al., 2005; De Pril et al. 2007). Decreased expression in N171-82Q mice in response to HDACi 4b was detected for other genes, including ubiquitin-like modifier activating enzyme 7 (Uba7) and SMT3 suppressor of mif two 3 homolog 2 (Sumo2) at 6 and 12 weeks treatment, respectively (Jia et al., 2012) (Table 7.3). The decrease in expression Sumo2 is notable, given that SUMOylation of proteins can lead to increased protein stability, such as in the case of Htt (Steffan et al., 2004; Wilkinson et al., 2010). In accordance with these gene expression changes, treatment of N171-82Q transgenic mice with HDACi 4b and another HDAC1/3-selective inhibitor, 874, resulted in the detection of fewer mutant Htt aggregates in different brain as measured by immunohistochemistry (Table 7.2). The decreased presence of aggregates was most notable in cortical regions, given that the striatum exhibited substantially fewer aggregates than cortical regions in this study (Jia et al., 2012). Consistent with these findings, Mielcarek and colleagues found that a the broadly acting HDAC inhibitor, SAHA, reduces SDS-insoluble aggregate load in the cortex and brain stem of R6/2 transgenic mice (Mielcarek et al., 2011). Similar reductions were not seen in the hippocampus, again implicating brain region–specific effects on aggregation. Other studies found that exposure to HDAC3-selective inhibitors, T247, T326, and T130, significantly reduced the levels of cytoplasmic Htt, but not insoluble Htt in the nucleus (Mano et al., 2014). In that same study, the authors reported that nonspecific HDAC inhibitors, TSA and SAHA, had very little effect on cytoplasmic or nuclear Htt aggregates in HeLa cells (Mano et al., 2014) (see Table 7.2). These findings are consistent with the notion that HDACi 4b treatment acts to promote ubiquitin-mediated protein degradation by either elevating the expression of genes associated with protein degradation or decreasing the expression of genes promoting protein stability.

HDAC Inhibitors in AD HDAC inhibitors have been shown in several recent studies to improve learning and memory deficits, as well as other disease phenotypes, in several different AD mouse models, making them a promising drug candidate for AD (Fischer, 2014). Along with improving behavioral symptoms, studies have shown striking effects of HDAC inhibitors to reduce amyloid beta levels, although the mechanisms for this effect are unclear. In many of these studies, the effects of HDAC inhibitors were shown to correspond to changes in histone acetylation levels and gene expression alterations, but in other cases, the effects of these drugs to improve disease protein clearance was not certain. Several studies have been conducted on Tg2576 transgenic mice, one of the most wellcharacterized, and widely used, mouse models of AD. These mice overexpress a mutant form of APP with the Swedish mutation, resulting in elevated levels of amyloid beta and ultimately amyloid plaques. In one study chronic administration of phenylbutyrate, starting before the onset of disease symptoms prevented age-related memory deficits in Tg2576 transgenic mice, in association with decreased amyloid beta pathology (Ricobaraza et al., 2011). Interestingly, these beneficial effects of this drug were also seen in aged, 12- to


174


16-month-old mice, when amyloid plaque deposition and major synaptic loss have already occurred. Reversal of learning deficits was associated to a phenylbutyrate-induced clearance of intraneuronal amyloid beta accumulation, which was accompanied by mitigation of endoplasmic reticulum stress and increased dendritic spine densities in hippocampal CA1 pyramidal neurons (Ricobaraza et al., 2012). In another study using the Tg2576 transgenic model, repeated treatment with gammahydroxybutyrate reduced cerebral amyloid beta levels in conjunction with improving memory deficits (Klein et al., 2015). The mechanism for this action was suggest to act via HDAC inhibition and upregulation of neprilysin, an enzyme involved in amyloid beta degradation (Klein et al., 2015). Studies found similar significant effects of a related inhibitor, betahydroxybutyrate in neural cell lines and an animal model induced by injecting amyloid beta into the hippocampus. Using histological examination, it was shown that beta-hydroxybutyrate effectively prevented amyloid beta deposition and neuron apoptosis in this rat model (Xie et al., 2015). A recent study evaluated the effect of MS-275, a class I HDAC inhibitor that shows selectivity toward HDAC1, in the APP/PS1 AD mouse model (Zhang and Schluesener, 2013). MS-275 was found to significantly reduce amyloid plaque deposition in the hippocampus and cortical regions (Zhang and Schluesener, 2013). Another study in APP/PS1 mice found beneficial effects after treatment with sodium butyrate at a later stage of the disease. In this study the authors observed that by HDAC inhibitor treatment caused an increase in histone acetylation and gene expression in various brain regions, but no effect on amyloid plaque pathology was observed (Govindarajan et al., 2011). Proposed mechanisms for these effects were not clear. Another study tested the effect of two novel HDAC inhibitors selective for class I or class II HDACs. Class II inhibitors administered to 3xTG AD mice that contain three mutations associated with familial AD (APP Swedish, MAPT P301L, and PSEN1 M146V), showed significantly reduced levels of both amyloid cleavage products, Aβ40, Aβ42, as well as Tau protein phosphorylated at threonine 181 (Sung et al., 2013). TSA treatment using the double transgenic APPswe/PS1mouse model of AD was found to increase the levels of β-secretase and γ-secretase activity in the brain, as well as increased levels of gelsolin, an antiamyloidogenic protein, in the hippocampus and cortex of the brain in AD Tg mice as compared to vehicle-treated mice. These effects were not associated with reduced amyloid load in the hippocampus and cortex, but did prevent the formation of new amyloid deposits, as might have been predicted based on increased β-secretase and γ-secretase levels (Yang et al., 2014).

HDAC Inhibitors and PD Models PD is another neurodegenerative disease in which HDAC inhibitors may represent a promising therapeutic strategy to ameliorate the progressive neurodegeneration. Several studies have investigated different HDAC inhibitors in worm, fly, and mouse models of the disease. Initial studies were carried out in a Drosophila model of PD. Administration of sodium butyrate or SAHA to flies expressing alpha-synuclein pan-neuronally showed rescue of



175

alpha-synuclein-induced neuronal loss in the dorsomedial neuronal cluster (Kontopoulos et al., 2006). Furthermore, these authors evaluated the role of histone acetylation in this effect, in light of the previous findings linking histone acetylation pathways to polyglutamine toxicity and possibly other types of neurodegeneration. These authors showed that alpha-synuclein binds directly to histones, reduces levels of acetylated histone H3, and inhibits HAT-mediated acetyltransferase activity (Kontopoulos et al., 2006). These findings implicated chromatin-related effects of alpha-synuclein in the degeneration associated with PD and also provided early evidence that administration of HDAC inhibitors could rescue alpha-synuclein-induced toxicity. The effects of the HDAC inhibitor, beta-hydroxybutyrate, has been tested in a C. elegans model of PD (Edwards et al., 2014). Worms expressing human α-synuclein fused to yellow fluorescent protein in the body wall muscle showed intense aggregation and fluorescence, which was significantly decreased in worms treated with beta-hydroxybutyrate (Edwards et al., 2014). Importantly, HDAC inhibitor treatment another study was linked to elevation in the expression of DJ-1, a gene associated with early-onset, autosomal recessive PD, in the Y39C alpha-synuclein transgenic mouse model of PD (Zhou et al., 2011). Mice treated with sodium phenylbutyrate showed increased DJ-1 expression and reduced alphasynuclein oligomer formation and aggregation in the cortex, striatum, and hippocampus (Zhou et al., 2011). Even in old mice, phenylbutyrate treatment greatly reduced the number of neurons with Lewy body-like inclusions (Zhou et al., 2011). These reductions in alphasynuclein aggregation were associated with improvements in age-related decline in motor and cognitive function (Zhou et al., 2011). Phosphorylated alpha-synuclein is thought to be important in the pathogenesis of PD, as alpha-synuclein deposits in PD are often phosphorylated (Fujiwara et al., 2002). Mouse studies using transgenic mice overexpressing human alpha-synuclein containing a double mutation (A30P+ A53T) found that sodium phenylbutyrate improved motor dysfunction in this mouse model (Ono et al., 2009). Correspondingly staining of alpha-synuclein in the brains of these animals revealed that phenylbutyrate significantly reduced the level of phosphorylated alpha-synuclein but not nonphosphorylated alpha-synuclein (Ono et al., 2009), adding further weight to the neuroprotective effects observed by sodium phenylbutyrate in this model. Although alpha-synuclein is generally considered to have a neurotoxic role in the pathogenesis of PD, there is evidence to suggest that the native endogenous unfolded alphasynuclein can have neuroprotective effects. A study using valproic acid demonstrated dose-dependent increases in the expression of endogenous WT alpha-synuclein in rat cerebellar granule cells (Leng and Chuang, 2006), an effect that was accompanied by dosedependent increase of acetylated histone protein H3 in the alpha-synuclein promoter and increased alpha-synuclein promoter activity (Leng and Chuang, 2006). Moreover, this increase in alpha-synuclein was accompanied by dose-dependent protection of these cerebral granule cells from glutamate-induced excitotoxicity. Similar findings by another group support these findings, whereby valproate administration was found to protect against 6-hydroxydopamine (6-OHDA) toxicity in cerebral granule cells by increasing alphasynuclein expression (Monti et al., 2010). These findings suggest that increased expression of


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normal alpha-synuclein, at the chromatin levels, plays an important role in the neuroprotective mechanism of valproate in PD.

CONCLUSIONS/FUTURE PERSPECTIVES The multitargeted effects induced by HDAC inhibitor treatment make these compounds an intriguing therapeutic option for neurodegenerative disorders. Their ability to promote clearance of misfolded or aggregated disease proteins is an especially relevant feature, in the case of proteinopathies, although the exact mechanisms for these actions are not certain. The approval of several classes of HDAC inhibitors for cancer treatment has opened the door for these compounds to be used for neurodegenerative diseases. Several safety and tolerability trials have already been conducted on phenylbutyrate in HD and amyotrophic lateral sclerosis, with similar studies currently being planned for SAHA in Niemann–Pick disease type C disease (see clinicaltrials.gov). These studies are paving the way for an encouraging discovery of new compounds that can treat these devastating disorders.

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C H A P T E R

8 The Role of Atg9 in Yeast Autophagy Henning Arlt and Fulvio Reggiori O U T L I N E Introduction 182 Structure and Role of Atg9 in Autophagy 183 Atg9 Trafficking via ER and Golgi Compartments 184 Atg9 Vesicles/Reservoirs Contribute to the Formation of the Preautophagosomal Structure 186

Atg9 Roles at the Preautophagosomal Structure 187 Atg9 Recycling From Autophagosomal Membranes 188 Concluding Remarks

189

Acknowledgments 190 References 190

Abstract

Cells make use of autophagy to turnover and recycle damaged or superfluous cellular components, and to adapt to nutrient deprivation conditions. The basic mechanism of this pathway is the sequestration of structures targeted to degradation by large double-membrane vesicles called autophagosomes. Genetic screens have identified numerous autophagy-related genes (ATG) that act during autophagosome biogenesis. Most of them are peripheral membrane proteins with Atg9 being the only conserved transmembrane protein essential for autophagy. Although the precise function of this protein is still unknown, Atg9 probably acts as a recruitment hub for several other Atg proteins at the site of autophagosome formation and as a result it is one of the factors playing a central role in autophagy regulation. Therefore understanding the molecular contribution of Atg9 to autophagy will be critical to unveil the molecular mechanism of this pathway. In this chapter we review the current knowledge about Atg9, with particular focus on the yeast Saccharomyces cerevisiae model and discuss open questions regarding this protein.


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8. THE ROLE OF Atg9 IN YEAST AUTOPHAGY

INTRODUCTION Macroautophagy, hereafter referred to autophagy, is a catabolic process conserved among eukaryotes that allows the degradation of intracellular components in the vacuole or lysosome (Hamasaki et al., 2013). This pathway thus eliminates unwanted cellular structures and organelles or serves as an adaptation to metabolic changes, especially those elicited by starvation conditions. Cellular constituents can be targeted by either unspecific bulk autophagy or autophagy receptors, which permit their specific downregulation (Stolz et al., 2014). These selective types of autophagy include the turnover of peroxisomes, endoplasmic reticulum (ER), mitochondria, and portions of the nucleus (Sica et al., 2015). In addition, yeast Saccharomyces cerevisiae has a constitutive type of selective autophagy that transports a subset of proteases into the vacuole, which has been termed the cytoplasm-to-vacuole targeting (Cvt) pathway (Lynch-Day and Klionsky, 2010). In yeast, autophagosome biogenesis occurs at the preautophagosomal structure or phagophore assembly site (PAS), which is usually localized adjacent to the vacuole limiting membrane and the ER (Graef et al., 2013; Kim et al., 2001; Suzuki et al., 2001, 2013). This compartment is formed de novo and initially consists of vesicles and possibly tubules (Mari et al., 2010; Yamamoto et al., 2012) (Fig. 8.1A). Upon induction of autophagy, membranes assembled at the PAS and probably fuse together to form the phagophore (or isolation membrane), a membranous cistern that grows by acquiring additional lipids through a mechanism that remains unknown. Fusion of the phagophore extremities via a membrane fission event leads to the sequestration of the cargo from the cytoplasm and the concomitant formation of a mature autophagosome, which subsequently fuses with the vacuole to deliver its content into the hydrolytic interior of this organelle (Fig. 8.1A). Elegant genetic screens in yeast have permitted to identify genes involved in autophagy, which have been termed ATG (Harding et al., 1995; Thumm et al., 1994; Tsukada and Ohsumi, 1993). Most of them compose the conserved core Atg machinery that mediates the formation of the phagophore and its expansion into an autophagosome (Hamasaki et al., 2013; Lamb et al., 2013; Reggiori and Klionsky, 2013). Genetic, biochemical, and cell biological analyses of the core Atg proteins have led to a hierarchical model for their assembly at the PAS (Suzuki et al., 2007). Even if their precise molecular roles remain unknown, these approaches have also allowed classification of the Atg proteins in functional modules, which act in concert during autophagosome formation. These modules include the Atg1 kinase complex, an autophagy-specific phosphatidylinositol 3-kinase complex and two ubiquitin-like conjugation systems (Hamasaki et al., 2013; Reggiori and Klionsky, 2013). Atg9, the only transmembrane protein within the core Atg machinery, is at the center of a fifth functional cluster, which also comprises Atg18 and Atg2. Atg9 is transported to the PAS at early stages of formation of this structure and interacts with several other functional Atg modules (Fig. 8.1A, Table 8.1). Atg9 remains associated with the phagophores and autophagosomes until these carriers fuse with the vacuole (Fig. 8.1A). As a result, Atg9 is one of the factors crucial for autophagy regulation and investigations on its trafficking will help to understand this key cellular pathway.


STRUCTURE AND ROLE OF Atg9 IN AUTOPHAGY

(A)

Atg9 vesicles

ER/Golgi

PAS

Phagophore

183

Auto phagosome

Vacuole

Atg9

(B)

Atg13-binding 1

316

Atg9

1

747 2

3

Atg17-binding

Atg9–GFP

Atg9 vesicles

6

Transmembrane domain

Atg11binding

(C)

4 5

997

Dimerization domain (766–770 aa)

mChe-Atg8

Merged

PAS

FIGURE 8.1 Molecular aspects of Atg9. (A) Transport pathways of Atg9 during autophagy. (B) Domain architecture of Atg9. The Atg9 dimerization motif is located at amino acids (aa) 766–770 (He et al., 2008). The Atg9 region between aa 2 and 302 is involved in the interaction with Atg17 (Sekito et al., 2009). Atg11 interaction domain is situated at aa 159–255 (He et al., 2006). Atg13 binding domain is positioned between aa 2 and 318 (Suzuki et al., 2015). (C) Subcellular distribution of endogenous Atg9-GFP after 1 h under nitrogen starvation. The mCherry-Atg8 protein marker allows to localize the Atg9 pool at the PAS. The mCherry-Atg8-negative Atg9 puncta represent Atg9 vesicles/reservoirs. The dotted white line indicates the cell contours. Size bar, 5 µm.

STRUCTURE AND ROLE OF Atg9 IN AUTOPHAGY Atg9 was identified in the initial screens for yeast S. cerevisiae mutants defective in autophagy (Thumm et al., 1994; Tsukada and Ohsumi, 1993) and Cvt pathway (Harding et al., 1995). Atg9 is the only conserved transmembrane protein among the autophagy machinery that is absolutely required for bulk autophagy (Noda et al., 2000) (Fig. 8.1B). It is also essential for all the selective types of autophagy that have been described so far including the Cvt pathway (He et al., 2006). It has no known structural domains except six central membrane-spanning segments with high conservation throughout eukaryotes (Young et al., 2006) (Fig. 8.1B). In contrast, its N- and C-terminal cytosolic extremities diverge between


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TABLE 8.1 Atg9 Physical Interaction Partners Interaction Partner

Method

Atg9 Region

References

AUTOPHAGY MACHINERY Atg2

IP

Full length

Wang et al. (2001)

Atg9

IP

C-terminus

He et al. (2008)

Atg11

IP, Y2H

N-terminus

He et al. (2006)

Atg13

IP

N-terminus

Suzuki et al. (2015)

Atg17

IP, Y2H

N-terminus

Sekito et al. (2009)

Atg18

IP

Full length

Reggiori et al. (2004)

Atg23

IP

Full length

Tucker et al. (2003)

IP

Full length

Legakis et al. (2007)

Y2H

Full length

Legakis et al. (2007)

Trs85

IP

Full length

Kakuta et al. (2012)

Cog3

Y2H

Full length

Yen et al. (2010)

Cog4

Y2H

Full length

Yen et al. (2010)

IP

Full length

Monastyrska et al. (2008)

Atg27 GOLGI TRAFFICKING

CYTOSKELETON Arp2

Methods: IP, immunoprecipitation; Y2H, yeast-2-hybrid.

species and are involved in the interaction with its numerous binding partners (Fig. 8.1B). In yeast Atg9 forms a stable complex with the cytosolic protein Atg23 and the single transmembrane protein Atg27 (Tucker et al., 2003; Yen and Klionsky, 2007) (Fig. 8.2A). Atg27 is only strictly required for pexophagy and the Cvt pathway, whereas bulk autophagy is only partially affected in atg27∆ cells (Yen and Klionsky, 2007).

Atg9 TRAFFICKING VIA ER AND GOLGI COMPARTMENTS In contrast to peripheral membrane-associated proteins, which can be directly recruited to the site of action from the cytosol, trafficking of a transmembrane component to and from autophagosomal membranes is a challenge for the cell and it has to be assisted by specific machineries. After synthesis and translocation into the ER, Atg9 reaches the Golgi very likely by COPII-coated vesicles (Graef et al., 2013; Mari et al., 2010). From there, it is delivered via Golgi membranes into vesicles and/or compartments that contribute to the formation of the PAS. On this route Atg9 makes use of several proteins of the secretory pathway


185

Atg9 TRAFFICKING VIA ER AND GOLGI COMPARTMENTS

(D) Rab activation

(A) Anterograde transport

GTP

Ypt1

GDP

Atg9 vesicle

PAS

TRAPIII Atg9 Atg23

Atg9

Atg27

(B)

(E)

Cargo-recognition Ape1 complex

Atg19

Atg1 Atg13

PAS

Atg11

P

Atg9

Recycling

Atg2

P P Atg9 P

PAS / autophagosome

Atg18

P

PI3P

P

(C) Kinase recruitment

Atg1 Atg13

P P Atg9 P

Atg17-Atg31-Atg29 PAS

FIGURE 8.2 Atg9 interactions. (A) Atg9 forms a stable complex with Atg23 and Atg27. (B) Atg9 recruits Atg11 to facilitate cargo-recognition at the PAS. (C) At the PAS, Atg9 binds the Atg1 kinase complex via Atg17-Atg31Atg29 trimer and is phosphorylated by Atg1. (D) Atg9 interacts with the TRAPIII complex at the PAS, which is required to activate the Rab GTPase Ypt1. (E) Recycling of Atg9 from the PAS and autophagosomes requires the function of Atg2 and Atg18, which both bind Atg9 directly. P, phosphate group; PAS, phagophore assembly site.

that are known factors in vesicle generation, targeting, and fusion (see below). Intriguingly, several Golgi proteins were shown to act in autophagy, although they were not identified as Atg proteins in the initial screens. One class of central regulators of numerous trafficking steps is the Rab GTPases, which act as recruitment hubs to orchestrate the formation and fusion of vesicles after their activation by specific guanine-nucleotide exchange factors (GEFs) (Hutagalung and Novick, 2011). Analysis of Atg9 trafficking has shown that the Golgi Rab Sec4 or its GEF Sec2 are required for efficient transport out of the Golgi (Geng et al., 2010). In agreement with this finding, generation of phosphatidylinositol-4-phosphate at the Golgi is also critical for release of Atg9 (Wang et al., 2012). Moreover the Golgilocalized Sec7 GEF and its downstream GTPases Arf1 and Arf2 are also crucial for Atg9 trafficking (van der Vaart et al., 2010). Atg23 and Atg27, the two proteins that form what appears to be a persistent complex with Atg9 (Legakis et al., 2007), play a role in its trafficking as well (Fig. 8.2A). Both are required to transport Atg9 from the Golgi to Atg9 vesicles/reservoirs, since Atg9 concentration on these


186


structures is reduced in atg23∆ and atg27∆ mutants (Backues et al., 2015). In particular, Atg9 is miss-sorted in the endosomal system and degraded in the vacuole in the absence of ATG27 (Yamamoto et al., 2012), suggesting a dynamic connection between the Atg9-positive compartments and endosomes as already evidenced (Ohashi and Munro, 2010). However, it remains unclear what the actual function of these two proteins is and whether they interact with factors involved in trafficking out of the Golgi or in other transport routes.

Atg9 VESICLES/RESERVOIRS CONTRIBUTE TO THE FORMATION OF THE PREAUTOPHAGOSOMAL STRUCTURE Atg9 localizes mostly on multiple cytoplasmic puncta that could not be assigned to any previously known organelle and were thus termed Atg9 reservoirs, Atg9 vesicles or Atg9 peripheral vesicles (Fig. 8.1C). These compartments emanate directly from the Golgi (Mari et al., 2010; Yamamoto et al., 2012), are positive for Atg23 and Atg27 (Tucker et al., 2003; Yen and Klionsky, 2007) (Fig. 8.2A), and are often found in close proximity to mitochondria (Mari et al., 2010; Reggiori et al., 2005). It remains unclear, however, whether mitochondria contribute lipids or other factors to the Atg9-positive membranes or whether under certain conditions regulate autophagy through Atg9 trafficking. Atg9 reservoirs contribute directly to the generation of the PAS by delivery of membranes to sites near the vacuole (Mari et al., 2010; Yamamoto et al., 2012). This site is often found in close proximity to ER exit sites (Graef et al., 2013; Suzuki et al., 2013), which could thus also contribute as a source for autophagosomal membranes. Anterograde transport of Atg9 to the PAS requires Atg23 and Atg27 (Legakis et al., 2007; Yen and Klionsky, 2007). It remains unclear, however, whether a single Atg9-positive vesicle or tubule matures into what will become the PAS or whether several of these membranous carriers fuse to generate this structure (Mari et al., 2010; Yamamoto et al., 2012). Biogenesis of one autophagosome does not require a high number of Atg9 vesicles and thus the Atg9 reservoirs are still the predominant localization in cells even under starvation conditions (Yamamoto et al., 2012) (Fig. 8.1C). Nonetheless the amount of Atg9 directly correlates with the frequency of autophagosome formation and this at least in part through the transcriptional control of the ATG9 gene (Jin et al., 2014). Atg9 has been shown to self-interact at Atg9 reservoirs, an event that is required for its efficient delivery to the PAS (He et al., 2008). It has been hypothesized that Atg9 might oligomerize to organize either vesicle budding or even fusion events at the PAS (He et al., 2008). On the other hand it is possible that multimerization of Atg9 actually determines the size of Atg9 vesicles, which have a typical diameter of 30–60 nm (Yamamoto et al., 2012), but experimental evidence for both hypothesis is lacking so far. Analysis of the hierarchical assembly of Atg proteins at the PAS has revealed that Atg11 and Atg17 are the initial factors that are recruited (Suzuki et al., 2007). Atg11 is required for selective types of autophagy in yeast, including mitophagy and the Cvt pathway (Kanki and Klionsky, 2008; Kim et al., 2001), where it directly interacts with the autophagy cargo receptors Atg32 and Atg19, respectively (Kanki and Klionsky, 2008; Okamoto et al., 2009; Shintani et al., 2002). Atg11 also binds directly to the N-terminus of Atg9 and this association is required to deliver Atg9 to the PAS (He et al., 2006) (Fig. 8.1B). As a result,


Atg9 ROLES AT THE PREAUTOPHAGOSOMAL STRUCTURE

187

it appears that the simultaneous binding of Atg11 to the autophagosomal cargo and Atg9 permits to coordinate the PAS and autophagosome formation in close proximity of the targeted cargo, in particular through the cross talk between Atg11 and the Atg1 complex (Kamber et al., 2015) (Fig. 8.2B). Furthermore, Atg9 delivery to the PAS depends upon binding to Arp2, which connects the Atg9 vesicles to the actin cytoskeleton (Monastyrska et al., 2008). Of interest, the direct interaction of Atg9 and Arp2 is blocked in an atg11∆ mutant, which further underlines an early requirement for Atg11 in Atg9 anterograde trafficking (Monastyrska et al., 2008). Under bulk autophagy-inducing conditions, Atg17 appears to substitute Atg11 in coordinating both Atg9 trafficking to the PAS and cross talk with the Atg1 complex (Fig. 8.2C), thus orchestrating autophagosome biogenesis (Cheong et al., 2008; Kabeya et al., 2005; Kamber et al., 2015).

Atg9 ROLES AT THE PREAUTOPHAGOSOMAL STRUCTURE The generation of the PAS and/or phagophore probably relies at least in part on fusion processes of Atg9-positive membranes involving SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins belonging to the secretory pathway (Nair et al., 2011). Rab proteins are also very likely participating in these events. The Rab Ypt1 gets activated at the PAS by its GEF, the TRAPIII complex (Kakuta et al., 2012; Lynch-Day et al., 2010). Activated Ypt1 interacts with multiple Atg proteins including the Atg1 kinase (Wang et al., 2013). Furthermore, Ypt1 is likely involved in the tethering of vesicles to generate the PAS or extend the phagophore in keeping with its role in fusion events at the Golgi apparatus (Lipatova et al., 2012; Tan et al., 2013; Wang et al., 2013). Interestingly, Atg9 directly binds to Trs85, the specific TRAPIII subunit at the PAS (Kakuta et al., 2012) (Fig. 8.2D). It is thus tempting to speculate that Atg9 initiates the activation of Ypt1 to induce tethering, fusion, and maturation at the PAS but it could also help to coordinate fusion of membranes derived from other organelles such as the ER (Sanchez-Wandelmer et al., 2015) (Fig. 8.2D). The conserved oligomeric Golgi (COG) tethering complex, which is known to be required for trafficking through the Golgi (Ungar et al., 2002), also localizes to the PAS providing additional evidence that tethering and fusion are required at this place for anterograde Atg9 transport (Yen et al., 2010). The COG complex was shown to interact directly with Atg9 in a yeast two-hybrid assay but the significance of this binding is still unclear (Yen et al., 2010). During bulk autophagy, Atg9 binds to Atg17, which is part of a trimeric complex consisting of Atg17, Atg29, and Atg31 (Kawamata et al., 2008; Sekito et al., 2009) (Fig. 8.2C). Structural analysis of this complex revealed a 10-nm crescent shaped dimer (Ragusa et al., 2012). It has been proposed that this complex could be involved in the tethering of Atg9 vesicles, as the radius of the dimer would fit with the curvature of the incoming vesicles. Direct evidence for this mode, however, is lacking so far. In addition to a putative role in tethering, the Atg17-Atg31-Atg29 complex is intimately connected to the Atg1-Atg13 kinase complex at the PAS (Mao et al., 2013; Stjepanovic et al., 2014). In particular, it recruits this kinase complex to the PAS through direct interaction between Atg29 and Atg13 (Stjepanovic et al., 2014) (Fig. 8.2C). Atg11 has a redundant role with Atg29 in the recruitment of the Atg1 complex (Fig. 8.2B) but while Atg11 principally


188


operates during the selective types of autophagy, Atg17 functions under nutrient deprivation conditions (Mao et al., 2013). Atg9 is a key player at this stage of PAS organization since it directly interacts with Atg13, Atg17, and Atg11 (Mao et al., 2013; Monastyrska et al., 2008; Sekito et al., 2009; Suzuki et al., 2015; Figs. 8.1B, 8.2B and C). It is likely that Atg1-Atg13 and the Atg17-Atg31-Atg29 complexes provide a scaffold at the PAS that allows recruitment and/or clustering of Atg9 vesicles since these complexes localize to the PAS independently and probably before Atg9 (Sekito et al., 2009; Suzuki et al., 2015). Furthermore the Atg17Atg9 interaction requires activity of the Atg1 kinase, which points toward a coordinated function of these different modules in the recruitment of Atg9 vesicles (Sekito et al., 2009). It cannot be excluded a priori that concentration of Atg9 at the PAS subsequently leads to more Atg1-Atg13 and Atg17-Atg31-Atg29 complex recruitment, in a sort of feedback loop, to further promote the formation of a phagophore. The Atg1 kinase is mostly inactive during normal growth conditions, but it is timely activated for selective types of autophagy by specific autophagy receptors that recognize cargo molecules. This cross talk is mediated by Atg11, which binds the autophagy receptors and in turn is able to activate Atg1, as has been shown for the Cvt pathway (Kamber et al., 2015). It remains unknown whether Atg9 is required for this activation, but the Atg1 complex and Atg11 need to localize to the PAS for activation and Atg9 directly binds Atg11. Therefore it is tempting to speculate that Atg9 could bridge or concentrate these factors to allow or to potentiate kinase activation at the PAS as described earlier.

Atg9 RECYCLING FROM AUTOPHAGOSOMAL MEMBRANES Atg9 is present on Atg9 vesicles and at the PAS (Fig. 8.1C). Because Atg9 does not appear to distinctively localize on the vacuole surface or gets degraded in this organelle, it is conceivable to hypothesize that this protein is recycled from either the PAS, autophagosomes, or directly after fusion of autophagosomes with the vacuole. This notion also supports a model of Atg9 cycling between its two main locations. Several mutant strains that accumulate Atg9 at the PAS have been identified suggesting which proteins might have a role in the recycling of this protein. Those include the Atg1 kinase, the autophagy-specific phosphatidylinotitol 3-kinase complexes, Atg2 and Atg18 (Reggiori et al., 2004) (Fig. 8.2E). Atg9 recruits Atg2 to the PAS (Wang et al., 2001). Atg18, on the other hand associates to the same location by simultaneously binding Atg2 and phosphatidylinositol-3-phosphate (PI3P) (Rieter et al., 2013). Fine mapping of these three proteins on giant Ape1 oligomers has revealed that they are concentrated at the edges of this cistern, while Atg1 is evenly distributed on the growing phagophore (Suzuki et al., 2013). It is thus possible that Atg9, Atg2, and Atg18 have a role in the closure of the autophagosome and/or Atg9 removal from the growing phagophore. Atg9 and Atg2 are both phosphorylated by Atg1 (Papinski et al., 2014). The phosphorylation of Atg9, in turn, is required for efficient recruitment of Atg18 to the PAS and thus the Atg1 complex could be a coordinator of putative Atg9 recycling (Papinski et al., 2014). In ypt7∆ or vam3∆ cells where autophagosome fusion with vacuoles is blocked; however, Atg9 is found on the accumulated autophagosomes suggesting that retrieval of this transmembrane protein takes place at least in part when these double-membrane vesicles are fusing with the vacuole (Cebollero et al., 2012; Yamamoto et al., 2012).


Concluding Remarks

189

Overall it still remains unknown whether Atg9 is recycled from more than one location and from which ones (PAS, autophagosomes, and/or vacuoles). The machinery for retrieval has also not been identified yet, but it is plausible that a vesicular carrier is what retrieves Atg9 back to the Atg9 vesicles/reservoirs or even to the PAS. There are evidences that the retromer complex, which is required for endosomal recycling of membrane proteins to the Golgi and plasma membrane (Seaman et al., 1998), could be involved in autophagy (Dengjel et al., 2012). This is of interest, since the retromer is known to deform membranes and sort cargo molecules, which is a function that would be required for Atg9 recycling and has not been identified among Atg proteins yet (Arlt et al., 2015; Chi et al., 2014). A direct role of this complex in autophagy and Atg9 trafficking, however, could not be detected so far at least in mammalian cells (Popovic and Dikic, 2014). Therefore it cannot be excluded that a different recycling system, independently or redundantly with the retromer, is mediating Atg9 retrograde transport.

CONCLUDING REMARKS Tremendous advances have been made in the last two decades on the molecular mechanisms of autophagy. Trafficking and regulation of yeast Atg9, in particular, has been deciphered in some detail leading to a good understanding about how Atg9 is delivered to the PAS and which functional interactions are carried out by Atg9 at this location. Atg9 trafficking to the PAS requires classical machineries, which are also used in the secretory pathway, in combination with Atg proteins like Atg23 and Atg27, which are in permanent complex with Atg9, and others such as Atg11 and Atg17 that only transiently interact. A crucial function of Atg9 appears to be the link to the Atg1 kinase complex through both direct interaction and also different bridging factors like Atg17 and Atg11. This connection is important for Atg9 anterograde transport, phagophore expansion, and probably also Atg9 recycling. Despite these conceptual progresses, several aspects of Atg9 function still remain unclear. An intriguing question is how Atg9 trafficking from vesicle pools to the PAS is regulated. Only few vesicles are required for one round of autophagosome formation and other membrane sources are thus very likely also involved. Another conundrum in the mechanism of autophagosome formation is the polar localization of the Atg9-Atg2-Atg18 complex to the edges of the growing phagophore. How is this peculiar distribution maintained and what is its actual function? Several possibilities are conceivable, which range from a role in autophagosome closure to putative recycling of Atg9 via a vesicular pathway. The latter hypothesis is especially interesting since to date it remains unclear how Atg9 is recycled, at which stage of autophagosome biogenesis it occurs, and to which compartment Atg9 is finally retrieved. Addressing these key questions on the role of Atg9 in autophagy using the yeast model system will be of relevance for the investigations in high eukaryotes as well. Atg9 trafficking prior to its delivery to the site of autophagosome formation seems to be even more diverse in mammalian cells (Popovic and Dikic, 2014; Puri et al., 2013). Given this complexity, a general understanding of the molecular mechanisms in yeast will provide new concepts for analyses in high eukaryotes.


190


Acknowledgments The authors thank Ruben Gomez-Sanchez, Muriel Mari, and Jaqueline Rose for the critical reading of the manuscript. F.R. is supported by ALW Open Program (822.02.014), DFG-NWO cooperation (DN82-303), SNF Sinergia (CRSII3_154421) and ZonMW VICI (016.130.606) grants.

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P A R T

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ROLE IN DISEASE 9 Methods for Measuring Autophagy Levels in Disease 195 10 Regulation of the DNA Damage Response by Autophagy 213 11 Autophagy and Cancer 237 12 ULK1 Can Suppress or Promote Tumor Growth Under Different Conditions 245 13 X-Box-Binding Protein 1 Splicing Induces an Autophagic Response in Endothelial Cells: Molecular Mechanisms in ECs and Atherosclerosis 259 14 Small Molecule–Mediated Simultaneous Induction of Apoptosis and Autophagy 269 15 Intestinal Autophagy Defends Against Salmonella Infection 291 16 Autophagy and LC3-Asscociated Phagocytosis Mediate the Innate Immune Response 303


C H A P T E R

9 Methods for Measuring Autophagy Levels in Disease Kanchan Phadwal and Dominic Kurian O U T L I N E Nanoparticles 202

Introduction 196 Methods of Measuring Autophagy in Disease 198 In Vitro Methods 198 Transmission Electron Microscopy 198 Immunoblots for LC3 and SQSTM1/p62 201 LC3 and p62 Immunohistochemistry 201 LC3 Fluorescence Microscopy 201 Tandem GFP-RFP-LC3 to Assess Autophagic Flux 202 Flow Cytometry–Based Methods 202

In Vivo Methods

203

Diseases 204 Cancer 204 Neurodegeneration 204 Infectious Diseases 205 Metabolic Diseases and Myopathies 206 Autoimmune Disorders 207 Emerging Trends

207

References 209

Abstract

Autophagy is a dynamic self-degradation process that plays a key role in many biological processes such as development, aging, and immunity. Emerging research in the area of cancer, neurodegenerative disorders, autoimmune disorders, infectious diseases, and myopathies have constantly shown link of autophagy with these disease etiologies. The field has grown in the last decade to include researchers from diverse areas of biology and medicine with a multitude of assay methods being developed. As with this recent surge in the interests, it is imperative to assess the quality and robustness of the assay methods used in the autophagy detection. In this chapter we have discussed some of the widely used methods available to study autophagy both in vitro and in vivo models with emphasis on disease states. Furthermore the scope of some of emerging methods to study autophagy in disease-specific scenarios is discussed. As a growing number of commercial companies are now actively engaged in developing assay reagents for autophagy, a summary of the major kits/reagents used in this surging field of autophagy are also provided.


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INTRODUCTION Autophagy (from the Greek auto, “self,” and phagein, “to eat”) is a process of cellular recycling of cytoplasmic contents via double-membrane vesicles called autophagosomes, which then fuse with the lysosomes and the contents released in the lumen are digested by lysosomal enzymes and released back into the cytoplasm. Three major types of autophagy are well-known: macroautophagy, microautophagy and chaperone-mediated autophagy. Macroautophagy is characterized by nonselective degradation of cytoplasmic cargo by double-membrane autophagosomes, which later fuse with lysosomes; microautophagy is mediated by direct engulfment of cargo into lysosomes; and the chaperone-mediated autophagy is facilitated by selective targeting of cargo by hsc70 and cochaperones via lysosome-associated membrane protein LAMP2A (Mizushima and Komatsu, 2011). This catabolic process is essentially a protective mechanism for the cells, faced by wide variety of stresses like nutrient starvation, misfolded proteins, dysfunctional organelles, oxidative stress, hypoxia and infection. This self-eating pathway essentially generates substrates like amino acids and free fatty acids for the tricarboxylic acid cycle and de novo protein synthesis (Rabinowitz and White, 2010). Autophagy is also involved in innate immune response as degradation of bacteria, protozoan, and viral pathogens can take place via autophagosome (called Xenophagy) in the infected cells (Conway et al., 2013; Orvedahl and Levine, 2009). Furthermore, autophagy has explicit role in removal of long-lived proteins, whole organelles like dysfunctional mitochondria, peroxisomes and the endoplasmic reticulum. Repercussions of accumulated misfolded proteins and dysfunctional organelles, oxidative stress, and hypoxia have been linked to the etiology of numerous diseases including neurodegenerative and metabolic disorders, cancer, heart diseases, infections and chronic inflammatory diseases such as Crohn’s. The sequential process of autophagy, starting from initiation of phagophore to mature autophagosome formation and finally its fusion with lysosomes involves over 30 autophagy-related genes (ATG), which were first identified in yeast and subsequently their homologues in human (Tsukada and Ohsumi, 1993; Klionsky et al., 2003). The pathway is signaled with inhibition of mammalian target of rapamycin (mTOR), the master regulator of stress signal in the cell. Transcription factor EB (TFEB) is another known key player of autophagic process as it coordinates the expression of several autophagy and lysosomerelated genes (Settembre et al., 2011). In general mTORC1 negatively regulates a complex consisting of UNC-51-like kinase 1(ULK1), ATG13, ATG101, and FIP200 and initiates the process of phagophore nucleation (Chan et al., 2007). This is followed by autophagosome elongation and maturation steps, which require two ubiquitin-like conjugation systems: the ATG5-ATG12 conjugation system and the microtubule-associated protein light chain 3 (LC3), ATG8 conjugation system (Ohsumi and Mizushima, 2004). The conversion of cytosolic diffused form of LC3 (LC3-I) to its lipidated and punctate form on the autophagosomal membrane LC3-PE (LC3-II) indicates autophagosome formation and is a hallmark of the autophagy process. These mature autophagosomes marked with LC3-II carry the cargo to lysosomes marked by lysosomal-associated membrane proteins like LAMP-1 and LAMP2. Several autophagy-“specific” receptors and adaptors like SQSTM1/p62, NBR1, PINK1, NDP52, VCP and optineurin have been identified and are linked to selective clearance of cargo-like dysfunctional mitochondria or protein aggregates (Fimia et al., 2013).

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The current research over the past decade has extensively associated the process of autophagy with pathophysiology of several diseases and aging. Its association in initiation and progression of cancer was established by the discovery of Beclin 1 (involved in initiation of autophagosome formation) as a haplo-insuffcient tumor-suppressor protein by Yue et al. (2003) and Qu et al. (2003). Major autophagy regulators such as UVRAG, bif1, Atg4C, Atg5 and Atg7 have been also assigned a tumor suppressor role in mouse models (Liang et al., 2006; Takahashi et al., 2007; Marino et al., 2007; Takamura et al., 2011). Although the pathogenesis of neurodegenerative disorder exhibits a progressive loss of neurons and neural function, this is strongly associated with mutations, impaired clearance of accumulated misfolded protein aggregates, and mitochondrial dysfunction (Jellinger, 2010; Goedert et al., 2010). For example, mouse models with mutations in induced putative kinase 1 (PINK1) and Parkinson protein 2 (PARK2) developed recessive familial forms of human Parkinson’s disease that showed extensive mitochondrial dysfunction (Morris, 2005; Trancikova et al., 2012) and both of these proteins signal the delivery of dysfunctional mitochondria to autophagosomes. Furthermore, it had been shown in mice that the macrophage-specific deletion of Atg5 increases their predisposition to Mycobacterium tuberculosis infection (Watson et al., 2012). In addition, several single nucleotide polymorphisms in genes regulated by autophagy have been revealed by human genomewide association studies, which predispose us to various infectious and inflammatory diseases. A list of autophagy genes and their association with disease is presented in Table 9.1. Given the decisive role of autophagy process in several human diseases, this chapter essentially discusses the experimental methods available to investigate autophagy, both in in vivo and in vitro models of disease. As this field is expanding rapidly, more contemporary methods to assess autophagy are being developed; thus it would be vital to highlight TABLE 9.1 A List of Autophagy Genes Associated With Human Disease Gene

Association

Disease

BECN1

Monoallelic deletion

Breast, ovarian and prostate cancer

UVRAG

Deletion

Colon cancer

ATG5

SNPs

Systemic lupus erythematosus, asthma

ATG16L1

SNPs

Crohn’s disease

NOD2

SNPs

Crohn’s disease, Mycobacterium leprae infection

IRGM

SNPs

Crohn’s disease, Mycobacterium tuberculosis infection

LAMP-2

X-linked deletion

Danon’s cardiomyopathy

SQSTM1/p62

Mutation

Paget’s disease

PARK2

Mutation

Parkinson’s disease, colon, lung and brain cancers

PINK1

Mutation


WIPI4

Mutation

Static encephalopathy of childhood, neurodegeneration

SPG15

Mutation

Hereditary spastic paraparesis type15

SNPs, single nucleotide polymorphisms.

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their advantages and limitations. Finally this chapter ends with some insight into topical advances in the technology, which could be garnered for developing novel assays in this emerging but fundamental area of science.

METHODS OF MEASURING AUTOPHAGY IN DISEASE Measuring autophagy can be challenging as it is a dynamic and multistep process. It becomes more challenging especially in in vivo systems. Two methods of autophagy measurements are commonly used; 1) measuring the autophagosomes at steady-state levels and 2) monitoring the autophagosome turn-over or the autophagic flux. Autophagic flux can be measured by blocking the downstream or upstream steps in the pathway by using chemical inhibitors. This can result in either the buildup of the lipidated-LC3 (LC3-II), i.e., the marker for autophagosomes, or the depletion of receptor protein p62/SQSTM1 which carries the cargo into the autophagosomes, indicating the cargo delivery and degradation via autophagosomes. The autophagy pathway can be blocked at various stages of the process, at the initiation of phagophore formation, autophagosome maturation, or autophagosome– lysosome fusion stage. Fig. 9.1 shows a diagrammatic representation of autophagy pathway and some of the commonly used inhibitors to study the dynamism of the process. Using a chemical inducer or an inhibitor in these experiments can reveal the state of autophagy in the disease model under investigation and could help in the interpretation of how a pharmacological compound is modulating this process in a disease. Table 9.2 is a list of commonly known inhibitors or inducers of the process, which can be used as a positive/ negative control for the measurement of the autophagic flux.

In Vitro Methods Over the last two decades several in vitro methods have been developed to study the autophagy process and these can be reliably implemented in disease models. For the proper interpretation of autophagy results, it is important to use specific inducers and inhibitors of the pathway, some commonly used ones are listed in Table 9.2. To facilitate in vitro studies, numerous commercially available kits have been developed by various providers. A list of readily available kits from different commercial providers to investigate the process of autophagy is given in Table 9.3. Widely used in vitro methods in autophagy research are discussed below. Transmission Electron Microscopy Transmission electron microscopy (TEM) is perhaps the oldest way of visualizing autophagosomes. Autophagosomes are double-membrane vesicles and TEM allows visualizing these conspicuous parallel membrane bilayers separated by an electron-lucent intramembranous space (Yla-Anttila et al., 2009). These double-membrane vesicles can be seen holding, either the cytosolic content or intact organelles like mitochondria, smooth endoplasmic reticulum and rough endoplasmic reticulum , ribosomes etc. or their bits. Autolysosomes are single-membrane structures and may not be readily distinguishable from other single-membrane organelles like endosomes or lysosomes (Beale et al., 2014) II. ROLE IN DISEASE

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FIGURE 9.1 The autophagy process and the some common inhibitors and inducers of the process. Source: Courtesy of Thévenod, F., Lee, W.-K., 2015. Live and let die: roles of autophagy in cadmium nephrotoxicity (review article). J. Toxics 3(2), 130–151.

TABLE 9.2 Some Common Chemical Inducers and Inhibitors of Autophagy Process Chemical

Mode of Action

Bafilomycin A1

Prevent fusion of autophagosome with lysosome

Chloroquine


Ammonium chloride


PepstatinA and E64D

Inhibit lysosomal proteases

Leupeptin

Inhibit lysosomal proteases

Vinblastine

Prevents trafficking of autophagosomes and lysosomes

Rapamycin

mTOR inhibitor

Resveratrol

SIRT1 activation

Spermidine

Induces autophagy by inhibiting acetyltransferase EP300

3-Methyladenine

Phosphoinositide 3-kinases inhibitor

Wortmanin


LY294002


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TABLE 9.3 A List of Autophagy Detection Kits From Different Commercial Providers Name of the Kit

Provider

CYTO-ID Autophagy Detection Kit

Enzo life sciences

VIVAdetect Autophlux Kit

Viva bioscience

Autophagy Detection Kit (ab139484)

Abcam

Autophagy Detection Kits

Thermo

VitroView In Situ Autophagy Detection Kit

Genecopoeia

Muse autophagy LC3-Antibody-Based Kit

Merck Millipore

Autophagy/Cytotoxicity Dual Staining Kit

Cayman chemicals

FlowCellect Autophagy LC3 Antibody-Based Assay Kit

Merck Millipore

Cell Meter Autophagy Assay Kit *Blue Fluorescence*

AAT bioquest

Autophagy Protein Detection Kit, BioAssay

US biologicals

FIGURE 9.2 HCT116 cells showing gold-labeled anti-GFP antibody bound to LC3 around double-membraned autophagosomes and single-membraned autophagolysosomes. Scale bars, 500 nm. LC3, light chain 3. Source: Adapted from Beale, R., Wise, H., Stuart, A., et al. 2014. A LC3-interacting motif in the influenza A virus M2 protein is required to subvert autophagy and maintain virion stability. Cell Host. Microb. 15, 239–247.

(Fig. 9.2). Recently, more emphasis is being given to quantification of the EM data (Kovács, 2014) and also toward accurate identification of the autophagosomes for a valid analysis. Resolution of autophagosomes structure under TEM can be enhanced with immuno-TEM with gold labeling (Mayhew, 2007). However, this could be difficult to achieve with LC3 antibody but using antibodies to target GFP in GFP-LC3 expressing cells could potentially solve this issue. New trends are emerging in the area of electron microscopy where one can study the three-dimensional morphology of autophagosomes using volume electron microscopy. This new method can reveal the ultrastructural details of autophagic compartments in the 3D space along with the details of the surrounding organelles. More details about these techniques can be found in the article by Biazik et al. (2015).

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Immunoblots for LC3 and SQSTM1/p62 Immunoblotting for LC3 (the marker for autophagosomes) is one of the popular techniques in the field. Among the different homologues of LC3 observed in mammals, LC3B is most common one. Endogenous LC3 exists in two forms, as mentioned earlier, LC3-I and LC3-II. Even though the molecular weight of LC3-II is higher than that of LC3-I owing to the addition of the lipid PE, LC3-II drifts faster than LC3-I on SDS-PAGE because of its extreme hydrophobicity. In general an increase in LC3-II to LC3-I band in the presence of autophagy inducers along with inhibitors of later stages (autophagolysosomes or lysosomes) of the process indicate an increase in autophagic flux when compared to conditions where no inducers and inhibitors were added. Mizhushima and Yoshimori (2007) published a review clarifying the interpretations of different scenarios one can come across while investigating autophagy. The conversion of LC3-I to LC3-II varies among the cell type, tissue, or the cell lines under investigation. Chunks of tissue from disease states for, for example, biopsies can be processed for immunoblots. These chunks can be divided into two lots, with or without lysosomal inhibitors and homogenized for the ex vivo flux assays. Some laboratories have successfully used liver and heart tissue for these assays (Kaushik and Cuervo, 2009; Gottlieb et al., 2015). Various precautions and standardization controls for these experiments are recommended in the guidelines by Klionsky et al. (2012). Combining immunoblots with microscopy techniques to check for punctate LC3 can provide more confidence in the results. Autophagic flux can also be investigated by immunoblotting for SQSTM1/p62 the autophagy receptor. A decrease in amount of p62 on autophagy induction could indicate the degradation of cargo via autophagosomes and could prove to be a very effective way of investigating the process. While working with primary cells in disease scenario, sometimes the amount of sample may be a limiting factor, however, flow cytometry based assays can help. LC3 and p62 Immunohistochemistry Though the methods for LC3 detection on immunohistochemistry (IHC) are recently being developed and optimized (Holt et al., 2011; Lee et al., 2012), p62 has been used for clinical IHC for quite a long time as a prognostic marker in many cancers and neurodegenerative disorders. IHC allows in situ examination of autophagy in various tissues under diseases settings. Development of epitope-specific antibodies has opened up new possibilities here. It has been reported as a cautionary note in the guidelines by Klionsky et al. (2012) that sometimes LC3 can be seen localized to structures other than autophagosomes in some of the tissues during IHC. As both LC3 and p62 are being considered hallmarks of autophagy process, there is less doubt that in the coming years IHC methods would be a very essential part of many clinical investigations. LC3 Fluorescence Microscopy Analysis of subcellular localization of endogenous punctate LC3 on autophagy induction can be followed by immunofluorescence microscopy and is indeed a very popular technique for investigation of autophagy in various settings. Alternatively recombinant form of LC3 tagged with GFP or other fluorescent proteins are being used for microscopy-based assays. Viewing the cells under confocal microscope for LC3 puncta can give more precise information than fluorescent microscopy. Measuring the number of LC3 puncta (either endogenous or GFP tagged) is necessary to reach a conclusion on the autophagy levels.

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It is recommended to count the number of LC3 puncta per cell rather than the total number of cells displaying puncta (Salazar et al., 2011). On this basis an average number of LC3 puncta in healthy/control cells can be compared to an average number of puncta under a given clinical condition under investigation. It has been demonstrated that using recombinant GFP-LC3 for microscopy can be unsuitable as the transfections can stress the cells and this can lead to upregulation of autophagy even in control cells and comparisons in a given setting can be inconclusive. Tandem GFP-RFP-LC3 to Assess Autophagic Flux Use of tandem monomeric RFP-GFP-tagged LC3 allows following the autophagic flux by live imaging. The GFP is sensitive to the acidic environment of the lysosomal lumen, whereas mRFP is tolerated and is stable there; hence colocalization of both GFP and mRFP signals (yellow dots) indicates it’s presence on the phagophore or an autophagosome but not an autophagolysosome (the signal will be only red dots) (Kimura et al., 2007). The major advantage of this system is in the disease models where instantaneous assessment of both induction of autophagy and the autophagic flux can be done in inherent conditions without using any inducers or inhibitors. Moreover, this method can be used to investigate autophagy in high-throughput drug screenings for various disease treatments. Quantification of “yellow only dots-autophagosomes” or “red only dots-autolysosomes” can now be achieved by using automated Cellomics microscopes, which can quantify these dots over a large number of cells in random microscopic fields. Flow Cytometry–Based Methods The novel multispectral imaging cytometry–based assays could be an ideal choice for investigating autophagy in primary immune cells in various diseases. These assays allow unbiased investigation of the process, both the snapshot and the flux in the presence of lysosomal inhibitors. With the use of different cell surface markers to label variety of immune cells, levels of autophagy can be measured in different populations by using autophagosomal and lysosomal markers (Phadwal et al., 2012; Phadwal, 2015). As it is a flow-based analysis, thousands of cells can be analyzed thus providing more statistical power to the analysis. Recently, Degtyarev et al. (2014) have developed a novel flow cytometry–based assay to quantitatively analyze autophagic vacuoles from a very limited amount of crude cell homogenates using specific organelle markers and dyes. These flow-based methods will allow researchers to have a statistically robust and high-throughput analysis of autophagy in limited samples especially in disease scenario. Nanoparticles One of the emerging trends is the use of nanoparticles in the investigation of autophagy. Labeled nanoparticles are being developed for both in vitro and in vivo studies. Fluorescent peptide–conjugated polymeric nanoparticles, which can be specifically cleaved by the Atg4 cysteine protease, loaded with lysosome staining dye have been used for the detection of Atg4 activity in both cell-free and cell culture settings (Choi et al., 2011).

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In Vivo Methods Several genetically modified mouse models targeting autophagy regulators are being developed and are invaluable tools to investigate the molecular mechanisms of autophagy in disease and drug development. Two main types of murine models are available in autophagy research: the reporter model system, which can both detect and quantitate autophagy in all tissues and organs in vivo, and the tissue-specific autophagy gene deletion models, which can result in a pathological condition or a disease. Transgenic disease mouse models expressing a fluorescent protein fused to LC3 are excellent tools to study autophagy both as snapshot observation and for measuring the autophagic flux. Some of the commonly used mice are mCherry-LC3 mice (Perry et al., 2009) and the GFP-LC3 mice (Mizushima, 2009). Furthermore, double transgenics using tandem GFP-RFP-LC3 mice are becoming a popular tool to study autophagic flux in vivo. In the GFP-LC3 transgenic models autophagic flux can be blocked in mice by treating the mice intraperitoneally with lysosomal blockers like chloroquine, Leupeptin, or bafilomycin. Taking the advantage of differential pH sensitivity of RFP and EGFP, Li et al. (2014) developed a CAG-RFPEGFP-LC3 mice, which allowed them to differentiate between early autophagosomes and late autophagolysosomes. Using these mice, they investigated the dynamics of autophagy in postischemic kidneys. Levels of autophagy can also be examined in vivo by labeling autophagosomes and autolysosomes with monodansylcadaverine (MDC) (Perry et al., 2009). MDC autofluoresces and integrates in lipid rich membranes of these vesicles. Latest improvements in microscopic imaging platform technology combined with the advances in optical biosensors and image analysis softwares have increased the opportunities of in vivo imaging applications in disease models. Noninvasive in vivo imaging and highresolution intravital imaging of mouse models has been implicated in various disease settings. Fluorescence molecular tomography and a cathepsin-activatable fluorochrome have been used in heart (Chen et al., 2013). A list of animal models with tagged autophagy genes are listed in Table 9.4.

TABLE 9.4 A List of Animal Models With Tagged Autophagy Genes Model

Species

References

GFP-LC3

Mice

Mizushima (2009)

GFP-RFP-LC3

Mice

Perry et al. (2009)

CAG-RFP-EGFP-LC3

Mice

Li et al. (2014)

GFP-LC3

Zebrafish

Hosseini et al. (2014)

GFP-LGG-1

C. elegans

Melendez et al. (2003)

UASp-GFP-mCherryDrAtg8a

Drosophila

DeVorkin and Gorski (2014)

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DISEASES Numerous seminal works have clearly demonstrated the role of autophagy in successful maintenance of cellular homeostasis, from reticulocyte maturation, antigen presentation, clearance of protein aggregates, and pathogens to clearing away the reactive oxygen species. Mutations in the form of SNPs or downregulation of major autophagy genes has been linked to several diseases like cancer, neurodegenerative diseases, metabolic disorders, autoimmune disorders, infectious diseases, and various cardiomyopathies. This part of the chapter will describe some of the most recent methods used to investigate autophagy in some of the main diseases and disorders.

Cancer Multiple clinical trials are underway targeting autophagy in cancer treatment. The role of autophagy as a double edged sword in tumorigeneis (tumor suppression and tumor survival) is constantly under surveillance and is investigated by many researchers. Many cancers like human breast, ovarian, and prostate cancer show a decreased Beclin 1 expression (Laddha et al., 2014) also Atg5 gene has been reported as a tumor suppressor in mouse models. In vitro assays for immunofluorescence and immunoblotting for LC3 and p62 are commonly used to study the process in cancer cell lines. To understand the role of autophagy in cancer development, cell lines and xenograft mouse models are central tools. Recently, genetically engineered mouse models (GEMMs) with tumor-specific ablation of autophagy genes have been developed by various groups. This has allowed the investigation into the dual role of autophagy during cancer progression. Rosenfeldt et al. (2013) developed a GEMM for pancreatic cancer where they could study the process by either ablating Atg5 or Atg7 with in the pancreatic tumors. Karsli-Uzunbas et al. (2014) developed an inducible model of systemic Atg7 ablation, which they later used to study lung cancer. Also Chen and Guan (2013) developed a novel approach by inactivating Atg7 at different stages of oncogenesis in a mouse lung cancer model.

Neurodegeneration Neurodegeneration is progressive degeneration of neurons which takes place in several diseases such as amyotrophic lateral sclerosis, Alzheimer’s, Huntington’s, Parkinson’s, and Prion diseases. Accumulation of misfolded protein as protein aggregates is the basis of the pathology of most of these neurodegenerative disorders. Autophagy impairment has been suggested as one of the reasons for these accumulations for long, but now the evidence in this direction are emerging. Specific inhibitors of autophagy in brain cells and better methods to measure autophagic flux are currently being investigated. Brain tissues are more suitable for IHC or immunoblot-based autophagy investigations. Recent advances have been made toward developing in vivo methods to study the process in neurons. Winslow et al. (2010) used mammalian cells and transgenic mice to show that alpha-synuclein overexpression impairs macroautophagy in these models of Parkinson’s diseases. Underwood et al., (2010) used fly and zebra models of Huntington’s disease to study the autophagy blocking properties of some anti-oxidants. Castillo et al. (2013) have

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FIGURE 9.3 AAV-mediated delivery of the autophagy flux reporter mCherry-GFP-LC3 into neonatal mice by ICV injection. AAV, adeno-associated virus; ICV, intracerebroventricular; LC3, light chain 3. Source: Courtesy of Matus, S., Valenzuela, V., Hetz, C., 2014. A new method to measure autophagy flux in the nervous system. Autophagy 10(4), 710–714.

developed a new method in mice, which delivers and express an autophagy flux reporter through the peripheral and central nervous system of mice by the intracerebroventricular delivery of adeno-associated viruses into newborn mice. Authors observed a widespread expression of a monomeric tandem mCherry-GFP-LC3 in neurons and this allowed the effective and precise measurements of LC3 flux using modulators of autophagy like rapamycin in axonal damage diseases (Fig 9.3). This simple method may now allow the expression of other autophagy pathway proteins like p62 or LAMP-2, which are involved in selective clearance of protein aggregates via the autophagy pathway in the neurons. A recent systems biology–based approach dementia-related disease genes has revealed autophagy as centrally dysregulated pathway (Caberlotto and Nguyen, 2014). Additional tools and models will be required for understanding the molecular basis of this dysregulation in these misfolded protein diseases.

Infectious Diseases Autophagy has a vital role in innate defence against various infectious agents. Xenophagy (clearance of microorganism via autophagy) is an important way of eliminating harmful microbes (Bauckman et al., 2015). However, many microbes can utilize and exploit autophagy machinery of the host for replication and survival (Huang and Brumell, 2014). Thus, it is essential to have precise methods to study host–pathogen interactions in autophagy compartments, which will enable to develop methods and new strategies for the therapeutic interventions in these diseases. Mostowy et al. (2013) developed Zebrafish larve as a model for the in vivo study of Shigella flexneri interaction with phagocytes and bacterial autophagy. They infected transgenic GFP-LC3 zebrafish larvae with Shigella and with the help of live microscopy they could demonstrate that the GFP-LC3 was recruited to intracellular Shigella, which was confirmed by ultrastructural studies using electron microscopy.

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Similar results have also been seen with Mycobacterium marinum, a natural fish pathogen. A convenient method using high-resolution imaging of microbial infection in zebrafish larvae by injecting pathogens into the tail fin was developed by Hosseini et al. (2014). Using this method they could study the autophagy response to M. marinum infection. They also demonstrated the association of M. marinum with GFP-LC3-positive vesicles during the course of mycobacterial infection. Along with visualizing autophagosomes, they could also see the presence of the mycobacteria in the autophagolysosomes, positive for both the lysosome markers LyTR and GFP-LC3. This new approach of using tail fin infection model could open up new research avenues in infectious disease studies.

Metabolic Diseases and Myopathies Autophagy is emerging as a key player in maintaining the metabolism in the cells. Recent findings have shown a prominent role of autophagy in maintaining cellular energy stores, lipid metabolism, intracellular hormone levels, glycogenolysis, and glucose homeostasis. As this novel role of autophagy is under scrutiny, it would of interest to discuss the available means to monitor autophagy in various metabolic disorders and physiological systems. As many of the metabolites are processed via lysosomes, it is important to study their flux through the autophagy pathway to reveal the net amount of the metabolite processed via lysosomes per unit time and in this scenario steady-state information will be of less use. Apart from the regular in vitro assays based on EM, immune fluorescence, and Immunoblotting for LC3 and p62, monitoring autophagy in metabolic disorders needs a care full analysis of lysosomes. Some of the important markers of lysosomes are the LAMP-1 and LAMP-2, the transmembrane lysosomal proteins and cathepsins. LysoTracker, which is a fluorescent dye is a useful tool to detect abnormalities within lysosomes (Eskelinen et al., 2004) and also the efficiency of autophagolysosome formation in live cells (Gonzalez-Polo et al. 2005). Subcellular fractionation of autophagosomes and lysosomes for analysis of these vesicles has been performed on brain (Liao et al., 2007) and liver (Cao et al., 2012) from mice as well as from cultured fibroblasts (Eskelinen et al., 2004). Detailed protocols can be obtained from Raben et al. (2009). Crinophagy is a type of autophagy where secretory granules are cleared by autophagosomes, thus controlling the intracellular hormone levels in the pituitary glands. Dysregulation of crinophagy can lead to diabetes and infertility (Weckman et al., 2014). Marsh et al. (2007) have investigated the role of crinophagy using pancreatic β-cells as a model in Rab3A−/−mouse (an animal model of deficient insulin secretion) to study the balance between insulin production, secretion, and degradation. Glycogen autophagy is an upcoming area of research, several muscular diseases show accumulation of glycogen-containing autophagic and lysosomal vesicles, for example, Pompe disease, Danon disease, infantile autophagic vacuolar myopathies, and chloroquine (CQ)-induced myopathies. Zirin et al. (2013) have developed an in vivo system using Drosophila melanogaster larvae to study the role of autophagy in glycogen metabolism in skeletal muscles. They used CQ to induce autophagic myopathy. Using this model they demonstrated that by knocking down muscle Glycogen synthase (GlyS) in D. melanogaster,

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they could block the formation of CQ-induced autophagosomes. Hopefully in future this model could be used to study the role of autophagy in other myopathies. LAMP-2-deficient mice were developed by Tanaka et al. (2000) and they used it as a tool to study cardiomyopathy. Using EM they observed extensive accumulation of autophagic vacuoles in liver, pancreas, spleen, kidney, skeletal, and heart muscle. Furthermore, they could observe ultrastructurally abnormal myocytes and reduced contractility in these mice. Similar phenotype is observed in Danon disease, which is a menifestation of LAMP-2 deficiency (Endo et al., 2015). Electron microscopy has extensively been used for making a diagnosis of autophagic vacuolar myopathies in patients treated with chloroquine, hydroxychloroquine and colchicine. Lee et al. (2012) improved the speed and accuracy of clinical diagnosis of these myopathies by developing an LC3 and p62 IHC-based method.

Autoimmune Disorders There is a growing evidence toward the alteration of autophagy in autoimmune disorders such as systemic lupus erythematosus, inflammatory bowel disease, rheumatoid arthritis (RA), psoriasis and multiple sclerosis. Anomalies in antigen presentation have been proposed to play an important role in autoimmune diseases. Role of macroautophagy in delivery of cytosolic and nuclear antigens to MHCII molecules is well discussed. Recent studies are also pointing toward a prominent role of lysosomes in these diseases. A very recent study has investigated autophagy in B cells from the blood samples of SLE patients and SLE mouse models using multispectral flow cytometry (Clarke et al., 2015). Lin et al. (2013) have investigated the role of autophagy in human RA and murine inflammatory arthritis and the function of autophagy in TNFα-mediated bone destruction in osteoclasts. They used hTNFαtg mice and reconstituted their bone marrow (post irradiation) by intravenous injection of Atg7fl/fl × LysMCre− Bone Marrow cells (BMCs), or Atg7fl/fl × LysMCre+ BMCs or BMCs transduced with lentiviruses encoding Beclin 1 (LVBeclin 1), or lentiviral control vectors (LVscramble). This methodology allowed them to analyze the role of autophagy in osteoclast differentiation, bone resorption, and how TNFα affects autophagy in murine osteoclasts both in vivo and in vitro. Similar strategies could work in other disease models to understand the role of autophagy in underlying pathologies at tissue level.

EMERGING TRENDS Rapid assays and use of minimal sample to analyze autophagy is an emerging need in autophagy research, importantly in the area of disease. Enzyme-linked immunosorbent assays (ELISA)-based kits for autophagy are being developed which are quantitative, do not require any expensive instrumentation, and are quick and high throughput. Enzo life sciences have developed a high-sensitivity ELISA kit for quantifying levels of Grp78/ BiP, which they claim could aid the study of autophagy in unfolded protein response,

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cancer, and neurodegenerative diseases. Most of the techniques we have discussed above are either invasive or are requiring genetic manipulation. New trends are emerging where the process of autophagy can be studied noninvasively. One such method is using Raman microspectroscopy, which allows nondestructive analysis of living cells. Konorov et al. (2012) used Raman microspectroscopy to study autophagy in starved MCF-7 cells. Mathematical modeling of autophagy pathways is another novel area of research. This system biology–based approach could lead to better understanding of the role of autophagy process in disease. One such model showing interaction between autophagy and apoptosis in mammalian cells has been developed by Tavasolly et al. (2015). We hope that in future these studies can lead to better understanding of the cell fate decisions mediated by autophagy in disease-specific scenarios and also how various modulators can impact these decisions. Mass spectrometry–based proteomics offers suitable platform for the dissection of various biochemical and signaling pathways, in both in vitro and in vivo systems. With the advent of modern mass spectrometers with ultrahigh resolution and sensitivity, this technology has now advanced from mere cataloging of proteins to accurate and in-depth quantitative analysis of complex protein mixtures that can be applied in a variety of different ways to address biologically relevant questions (protein expression analysis, protein–protein interactions, PTMs, proteome turn over). Still, under sampling could occur when the number of peptides in sample substantially exceeds the sequencing speed during MS data acquisition. Targeted mass spectrometry, however, alleviates this problem by selectively targeting peptides derived from proteins of interest by selected/multiple reaction monitoring (S/MRM). Employing S/MRM-based analysis, all the proteins involved in autophagy pathway for instance, could be selectively and reproducibly quantified. However, assay generation could be time consuming as this involves creating suitable transitions of product and precursor ions of the proteotypic peptides. From a clinical/disease perspective, it is vital to develop assays for limited amount of samples, for example, such as tissue biopsy, together with multiplexing capabilities to analyze large number of samples from a disease population. A novel MS-based strategy called SWATH-MS (Gillet et al., 2012) looks highly attractive in this respect. This is a data-independent acquisition MS method, which allows complete and permanent recording of all the detectable fragment ion spectra that once acquired may be perpetually interrogated in silico to test a new hypothesis. Such data sets offer unique possibility for cross-study comparisons at a population level that are not anticipated at the time of MS data acquisition. Rosenberger et al. (2014) generated a compendium of highly selective assays for more than 10,000 human proteins enabling their targeted analysis by SWATH-MS. This data set contains majority of the autophagy-related proteins listed in Table 9.1, indicating their potential usefulness once SWATH-MS data sets are acquired from clinical samples. Guo et al. (2015) employed SWATH-MS technology for the rapid conversion of tissue biopsy samples into permanent digital proteome maps, which distinguished tumor kidneys tissues from healthy ones and identified distinct kidney cancer subtypes. With the continual technological advances, it may be speculated that targeted proteomics methods will increasingly offer translational value in the field of autophagy and diseases with its applications in clinical research and biobanking.

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C H A P T E R

10 Regulation of the DNA Damage Response by Autophagy Vinay V. Eapen, David P. Waterman, Brenda Lemos and James E. Haber O U T L I N E Selective Autophagy

Introduction 214 The DNA Damage Response (DDR) in Higher Eukaryotes 215 Types of DNA Damage 215 DNA Damage Checkpoint 215 DNA Damage Checkpoint Signaling 216 The DDR in Budding Yeast 218 Repair of DNA Damage Double Strand Break (DSB) Repair Nonhomologous End Joining Homologous Recombination

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The Autophagy Pathway in Higher Eukaryotes 220 The Autophagy Pathway 220 Regulation of Autophagy in Yeast and Mammals 221

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Mitophagy 223 Pexophagy 224 Chaperone-Mediated Autophagy 224

Autophagy and DNA Damage—A Complex Cross Talk A DNA Damage–Induced Autophagy Pathway ATM—A Diverse Kinase With Roles Outside of the Nucleus Autophagy and Senescence Autophagy Regulation of the DDR Conclusions and Perspectives

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Acknowledgments 232 References 233

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10. Regulation of the DNA Damage Response by Autophagy

Abstract

Several cellular survival pathways help buffer cells against environmental stresses. The DNA damage response (DDR) activates a highly conserved signaling cascade that (1) enforces cell cycle arrest and (2) promotes the repair of DNA lesions. The autophagy pathway primarily aids cellular survival under conditions of poor nutrient availability by scavenging internal reserves of macromolecules in order to recycle molecular building blocks. Autophagy can also target the degradation of specific substrates, including damaged organelles and proteins. Communication between these pathways has been a recent focus of investigation. In this chapter we review the connection between the DDR and autophagy with a special emphasis on the molecules that mediate this cross talk and the physiological relevance of this phenomenon.

INTRODUCTION Maintenance of genome integrity is a critical part of cellular physiology. The incidence of oxidative DNA lesions in each human cell can be as high as 105 per day (Hoeijmakers, 2009) and vertebrate cells accumulate dozens of chromatid breaks during each round of DNA replication (Sonoda et al., 2006). Therefore, effective mechanisms for recognizing and responding to genotoxic stress are critical for cellular survival. This phenomenon, collectively termed as the DNA damage response (DDR), is responsible for the detection and repair of DNA damage. The DNA damage checkpoint is a signaling cascade that is initiated by DNA damage and triggers cell cycle arrest to allow enough time for repair to take place. DNA damage–induced cell cycle arrest is initiated by two PI3-like kinases, ATM (Ataxia Telangiectasia mutated) and ATR (Ataxia Telangiectasia mutated and Rad3 related), which are activated by direct binding to the sites of DNA damage and initiate a cascade of phosphorylation events on numerous downstream effector proteins (Ciccia and Elledge, 2010; Harrison and Haber, 2006). Many of these proteins have obvious connections to the DDR, such as those involved in cell cycle progression and DNA repair. However, recent proteome wide studies of substrate phosphorylation by ATM and ATR have revealed that numerous, diverse and unexpected targets may be directly modified in response to DNA damage (Matsuoka et al., 2007). These proteins belong to various functional categories relating to protein metabolism, cytoskeletal functions, and developmental processes (Matsuoka et al., 2007). In addition, ATM/ATR signaling in higher eukaryotes converges onto the master transcriptional regulator p53 to mediate the transcriptional upregulation of numerous genes, including those involved in autophagy (Kenzelmann Broz et al., 2013). Therefore the DDR is a coordinated response of multiple stress response pathways, which ensures survival in the face of DNA damage. Like the DDR, autophagy is another highly conserved stress responsive pathway. The classical definition of autophagy describes a catabolic phenomenon, activated under conditions of low nutrient availability. Autophagy ensures the recycling of internal metabolites, such as amino acids, by self-digestion of proteins or even whole organelles in the lysosome (Mizushima et al., 2011; Reggiori and Klionsky, 2013). As such, autophagy is often thought of as a degradation pathway activated by nutrient depletion; however, this is a narrow definition and ignores the fact that autophagy can also regulate the targeting of proteins to appropriate subcellular locations and can also be activated by signals other than nutrient availability. Most notably for our discussion, genotoxic stress has been shown to induce autophagy and autophagy-deficient cells have been shown to have higher levels of DNA II. ROLE IN DISEASE

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damage (Yang et al., 2011). As we will review below, recent studies both in mammals and in budding yeast have shown that DNA damage–induced autophagy controls the levels of various cell cycle and DNA repair enzymes and therefore is critical for robust cell cycle arrest and accurate repair after DNA damage (Dotiwala et al., 2013; Liu et al., 2015; Park et al., 2015). The molecular connections between the DDR and autophagy remain largely unexplored; however., some core principles have emerged. First, DNA damage–induced autophagy requires some core components of the DDR pathway, such as ATM and p53, and has been observed in response to a variety of DNA-damaging agents (Vessoni et al., 2013). However, it is not yet clear which pathway of autophagy is being induced and if the roles of these proteins are specific to DNA damage or have functions in general autophagy. Second, only a handful of proteins have been identified as autophagy substrates after DNA damage and how these proteins are targeted for degradation by autophagy remains unknown. Finally, there have been conflicting reports on the physiological relevance of damage-induced autophagy, i.e., whether it promotes or impairs survival. In this chapter, we review the current knowledge on these questions and frame some of the main questions that remain to be answered.

THE DNA DAMAGE RESPONSE (DDR) IN HIGHER EUKARYOTES Types of DNA Damage DNA can be damaged from both endogenous and exogenous sources. Endogenous perpetrators of DNA damage include byproducts of metabolic processes resulting in alkylation, hydrolysis, and oxidation. During replication the DNA double helix can also be broken by replication fork stalling, by the presence of unrepaired single-strand DNA (ssDNA) nicks or by the misincorportation of mismatched bases or ribonucleotides. Exogenous sources of DNA damage include ultraviolet (UV) radiation, ionizing radiation (IR), and various chemical agents. These genotoxic agents can result in different types of damage that include DNA intra- and interstrand cross-links, cross-links between DNA and proteins, and both single and double strand breaks (DSBs) (Mehta and Haber, 2014; Sancar et al., 2004). If not properly repaired, DNA damage can lead to genomic instability, cellular apoptosis, or senescence. Genome instability can lead to aging defects, neurodegenerative diseases, and cancer. Thus, cells have evolved coordinated DNA damage checkpoints and repair pathways in order to prevent genomic instability (Ciccia and Elledge, 2010; Harrison and Haber, 2006).

DNA Damage Checkpoint The DNA damage checkpoint provides the cell with an opportunity to stall cell division such that an effective DNA repair effort can be mounted. Blocking cells prior to mitosis prevents cells from transmitting broken chromosomes to a daughter cell and from losing acentric chromosome fragments. Deficiencies in DNA damage checkpoint proteins have a profound impact on genome stability. Many of the processes and proteins were initially identified and characterized in fission and budding yeast; however, here we maintain a mammalian cell focus, but will note key evolutionarily conserved findings in budding yeast (Table 10.1). II. ROLE IN DISEASE

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TABLE 10.1 Proteins Involved in the DNA Damage Checkpoint Mammals

Yeast

Rad17

Rad24

Rad9

Ddc1

Rad1

Rad17

Hus1

Mec3

BRCA1

Rad9

TopBP1

Dpb11

Mre11

Mre11

Rad50

Rad50

Nbs1

Xrs2

ATR

Mec1

ATM

Tel1

PIKK binding partner

ATRIP

Ddc2/Lcd1

Effector kinases

Chk1

Chk1

Chk2

Rad53

SENSORS 9-1-1 clamp and clamp loader

BRCT-containing

MRX complex

TRANSDUCERS PI3-kinases (PIKK)

DNA Damage Checkpoint Signaling The DNA damage checkpoint depends on two members of the Phosphatidylinositol 3-kinase-like kinase (PIKK) family: ATM and ATR (see Table 10.1 and Fig. 10.1). ATM/ ATR phosphorylate a large number of proteins on serine/threonine residues that are followed by glutamate (SQ/TQ). ATR responds to a variety of DNA lesions, while ATM primarily responds to DSBs (Harrison and Haber, 2006; Ciccia and Elledge, 2010). ATM is normally present in the cell as an inactive dimer, but is converted to an active monomer upon damage (Ciccia and Elledge, 2010). Activation of ATM requires the presence of the MRN complex consisting of a heterotrimeric complex of MRE11-RAD50-NBS1. After damage the MRN complex rapidly localizes to the site of the break and recruits ATM, in part by its interaction with the NBS1 C-terminal domain. ATR activation requires ssDNA, which can be generated by base- or nucleotide-excision repair (NER) or by the 5′ to 3′ resection of DSB ends. These ssDNA regions become coated by replication protein A (RPA), which binds the ATR-interacting protein (ATRIP). The association of ATR and ATRIP stimulates the phosphorylation and recruitment of the DNA damage-specific clamploading protein RAD17. Along with four small replication factor c (RFC) subunits (which

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are shared with the proliferating cell nuclear antigen (PCNA) clamp loader, RFC1), RAD17 acts as a clamp-loading complex for RAD9-HUS1-RAD1, which together are called the 9-1-1 complex. The 9-1-1 complex encircles DNA, resembling the PCNA sliding clamp, except that 9-1-1 sits at the junction of double-stranded DNA with a protruding 3′-ended singlestranded tail produced by 5′ to 3′ resection (Ciccia and Elledge, 2010). Both ATM and ATR can phosphorylate an isoform of histone H2A known as H2AX at the Ser139 position. Phosphorylated H2AX, referred to γ-H2AX, can spread over a megabase of DNA surrounding the DNA break. γ-H2AX chromatin promotes the recruitment of repair factors and increases the concentration of repair and checkpoint-related proteins around the DNA lesion. Notably the adaptor protein 53BP1 is recruited via its BRCT and Tudor domains to methylated histone sites around a DNA lesion. 53BP1-bound chromatin restrains DNA end resection and promotes checkpoint activation (Harrison and Haber, 2006). CHK1 and CHK2 are effector proteins in the checkpoint-signaling cascade that phosphorylate targets for cell cycle arrest. ATM primarily phosphorylates CHK2 in response to DBSs, while CHK1 is phosphorylated by ATR following UV radiation. During G1 and S phases of the cell cycle, either protein can inhibit replication after DNA damage by limiting the recruitment of replication proteins to the DNA (Stracker et al., 2009). CHK1 and CHK2 also control mitosis onset by stabilizing the CDC25 family of phosphatases (A, B, and C). Under a normal cell cycle, CDC25 phosphatases remove inhibitory phosphorylations from cyclin-dependent-kinases (CDKs). After DNA damage the CDC25s are negatively regulated by CHK1 and CHK2 through phosphorylation that inhibits the binding to target proteins, but allows binding of the SCFβTrcp ubiquitin ligase that targets CDC25A for degradation by the proteasome, which activates the intra S-phase checkpoint (Reinhardt and Yaffe, 2009). ATM and ATR also phosphorylate and activate the tumor suppressor protein, p53. Under normal conditions, p53 is maintained at low levels in the cell, regulated by the E3 ubiquitin ligase MDM2, and its transcription repressor MDM4. Activated p53 cannot interact with MDM2 and instead functions as a transcription factor affecting expression of a variety of downstream targets or it can fulfill its role independent of its transcription factor activity (Kastan et al., 1991). As a result, p53 can affect many cellular outcomes, including cell cycle arrest, DNA repair, senescence, and apoptosis. A consequence of transcriptional activity of p53 is the increased expression of p21. p21 acts as an inhibitor of cell cycle progression by inhibiting CDK/cyclin complexes, the PCNA, and cyclin B1 and by promoting retinoblastoma protein (pRB) degradation (Harper et al., 1993; Kastan et al., 1991). After the completion of DNA repair, cells need to turn off the DNA damage checkpoint in order for mitosis to proceed. This process is termed as checkpoint recovery. Cells can also inactivate checkpoint signaling despite the presence of unrepaired DNA in a process termed checkpoint adaptation (Bartek and Lukas, 2007; Syljuasen et al., 2006). Recovery and adaptation are genetically distinct processes and require the action of different proteins. Both processes require the action of protein phosphatases, such as Wip1. Wip1 removes the ATM/ATR phosphorylation of p53 and Chk1, thereby deactivating the DNA damage checkpoint (Shreeram et al., 2006). Similarly, depletion of Plk1 (Polo-like kinase1–Cdc5 in yeast) also impairs checkpoint recovery. Plk1 promotes checkpoint recovery by stimulating the degradation of the CDK inhibitory kinase Wee1. Adaptation in higher eukaryotes may also be carried out by the scaffold protein Claspin, which has been shown to downregulate CHK1 signaling in Xenopus laevis extracts in response to the replication inhibitor aphidicolin.

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The DDR in Budding Yeast In budding yeast the ATR homolog, Mec1, has assumed much of the burden on damage signaling, with only a minor role reserved for the ATM homolog, Tel1 (Harrison and Haber, 2006). Mec1 is recruited to the sites of DNA damage with the aid of Ddc2 (ATRIP). Cell cycle arrest, prior to anaphase, is principally mediated by Mec1-dependent phosphorylation of the CHK2 homolog, Rad53, which becomes autophosphorylated when it is associated with the Rad9 (53BP1) scaffold protein. In addition, Mec1 phosphorylates the Chk1 kinase. Signaling converges on inhibition of the separase enzyme that releases sister chromatids by cleaving cohesion. Similar to mammalian cells, yeast exhibit adaptation and recovery from the DNA damage checkpoint (Sandell and Zakian, 1993). Yeast cells suffering even a single DSB will arrest for the equivalent of five cell divisions if the break is not repaired, but then they adapt and resume cell cycle progression (Lee et al., 1998). If the DSB is repaired, the checkpoint is turned of by recovery. In both cases, Rad53 is dephosphorylated by the Ptc2/Ptc3 (PP2C) phosphatases and depletion of these phosphatases prevents mitosis after DNA damage (Leroy et al., 2003). In addition to nuclear-functioning enzymes, cytoplasmic processes can control adaptation and recovery. In budding yeast, mutations in the Golgi-associated retrograde transport pathway result in permanent cell cycle arrest after DNA damage (Dotiwala et al., 2013). This occurs in part due to autophagy-mediated mislocalization and degradation of mitotic activators such as securin and separase. Induction of autophagy directly by adding rapamycin or expressing a dominant-active allele of ATG13 also results in this phenotype (Dotiwala et al., 2013). These results suggest a key role for autophagy in checkpoint recovery, adaptation, and cell cycle progression after DNA damage.

REPAIR OF DNA DAMAGE DNA can sustain damage on one or both strands, and the type of damage incurred dictates the subsequent mechanism of repair. When damage is limited to just one strand, the lesion can be repaired through excision of the damaged region followed by DNA synthesis using the opposite strand as a template. These single-stranded forms of DNA damage—oxidation and other modifications of bases as well as misincorporation of ribonucleotides—are much more frequent than DSBs and are readily corrected by the cell, using either base-excision repair or NER mechanisms. However, lesions such as single-strand nicks and intrastrand cross-links can block replication; stalled replication forks can lead to the formation of DSBs and cause cell cycle delay through activation of the DNA damage checkpoint.

Double Strand Break (DSB) Repair Although DNA replication is remarkably accurate, vertebrate cells suffer on average a dozen, or more, sister-chromatid breaks every replication cycle. This is evident when the key Rad51 repair protein is depleted from chicken DT40 cells, from the frequency of sister-chromatid breaks (where one sister is intact and the other is broken) (Sonoda et al., 2006). Failure to accurately repair a DSB can result in chromosomal loss and genome

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rearrangements, chromosomal translocations and fusions. Unlike ssDNA damage, a DSB cannot be repaired by using the other strand as a template and instead, two major pathways are employed: nonhomologous end joining (NHEJ) and homologous recombination (HR). The decision of the cell to repair a DSB through either of these two pathways depends on the extent of DNA end processing, which is controlled in part by the cell cycle.

Nonhomologous End Joining The simplest form of DSB repair is NHEJ, as extensive DNA end processing is not required. Since NHEJ does not require a homologous sequence for repair, it is favored by cells in the G1 stage of the cell cycle, when sister chromatids are not available to provide an exact homologous sequence. Although diploid cells do have a homolog that could serve as a template to repair a DSB by HR, homologs are not paired and inter-homolog repair appears to be an inefficient event in mammals (Richardson et al., 1998). Since mammalian cells reside predominantly in G1, NHEJ is the favored repair pathway. NHEJ is initiated by binding of Ku70-Ku80 heterodimeric complex (herein referred to as Ku) to the broken ends (Lieber, 2010). Ku acts as both a molecular bridge and a scaffold as it serves to align and stabilize both ends, prevent extensive end processing, and recruit the serine/threonine kinase of the phosphoinositide 3-kinase (PI3K) family, DNA-PKcs. Formation of the Ku complex also recruits DNA ligase IV along with the accessory proteins XRCC4 and XLF. This complex reattaches compatible ends of the break through ligation. If the ends are incompatible in that they do not present overlapping complementary bases, end-joining can result in insertions or deletions within the immediate vicinity of the break, and in some cases, the deletions are produced using microhomologies at the junctions, in a process termed microhomology-mediated end joining (Lieber, 2010).

Homologous Recombination Once cells have progressed into and through S-phase, HR becomes the pathway of choice for DSB repair for two reasons. First, many proteins that are involved in HR require Cdkdependent phosphorylation for their activation (Ira et al., 2004). Second, the predominant spontaneous DSB lesion is a chromatid break, where a sister chromatid is available to serve as the optimal homologous template for repair. HR can be subdivided into several different categories depending on the type of repair process used. These include single-strand annealing, gene conversion, and break-induced replication. The mechanistic details of each of these repair pathways are described elsewhere (Mehta and Haber, 2014) but all HR-based repair events share the similar initial event of DNA end processing, which is the 5′ to 3′ nucleolytic degradation of the broken ends, a process termed DNA end resection. Resection begins by binding of the MRN complex (Mre11-Rad50-Nbs1) along with the endonuclease CtIP to the broken ends (Symington, 2014). Endonuclease activity of CtIP requires phosphorylation by Cdk and is thus inhibited in G1. Following this initial processing, more extensive 5′ to 3′ resection is accomplished by Exo1 or DNA2 nucleases. DNA2 is associated with a helicase complex composed of BLM-Top3-Rmi1-Rmi2. In budding yeast, initial resection often begins with the MRX complex (Mre11-Rad50-Xrs2), followed by extensive resection accomplished either by Exo1 or by the BLM homolog Sgs1, complexed with Top3, Rmi1, and Dna2 (Mimitou and Symington, 2008).

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As 5′ to 3′ resection proceeds, the exposed 3′ ssDNA is rapidly coated with the heterotrimeric RPA complex in order to prevent the exposed ends from forming secondary structures. RPA is readily displaced by Rad51 recombinase through deposition by BRCA2 in mammals, or by Rad52 in budding yeast. Formation of this helical Rad51 nucleoprotein filament along ssDNA allows for the broken end to search the genome for a homologous sequence to repair from, through the activity of Rad51. While in theory the Rad51 nucleoprotein filament is capable of searching the entire genome, in practice its search is influenced by the three-dimensional organization of chromosomes within the nucleus (Lee et al, 2015). Once a suitable stretch of homology is located, Rad51 facilitates strand invasion, the first step in repair of the DSB by HR.

THE AUTOPHAGY PATHWAY IN HIGHER EUKARYOTES All cells have mechanisms to control protein homeostasis through regulation of the rates of their synthesis and degradation. Protein degradation occurs in eukaryotes by either the ubiquitin–proteasome system or autophagy. The ubiquitin–proteasome system degrades proteins by covalently attaching ubiquitin molecules to target proteins, which stimulates their degradation by the proteasome. Ubiquitination of target molecules occurs by the concerted action of three classes of enzymes (E1, E2, and E3), acting sequentially, which are responsible for the activation, conjugation and ligation of ubiquitin to the target protein (Finley, 2009). Autophagy can be selective or nonselective; this distinction is based in large part on the cargo proteins that are being targeted for degradation. In budding yeast and higher eukaryotes, selective autophagy serves an important role in maintaining protein homeostasis by delivering proteins to the lysosome and by controlling the levels of various proteins. In addition to these roles, autophagy also serves to preserve the quality of cellular metabolism, by removing harmful protein aggregates and damaged organelles (Mizushima et al., 2011; Reggiori and Klionsky, 2013).

The Autophagy Pathway The most commonly described type of autophagy occurs after nutrient or energy deprivation and is referred to as starvation-induced macroautophagy, hereafter referred to as macroautophagy. This process ensures cellular survival in conditions of low nutrient availability by recycling internal reserves of macromolecules through their digestion in the lysosome/vacuole and occurs by the formation of double-membrane vesicles, termed autophagosomes, at phagophore assembly sites (PAS) in the cytosol (Feng et al., 2014; Reggiori and Klionsky, 2013). During macroautophagy, autophagosomes engulf apparently random portions of the cytosol and deliver them to the lysosome for subsequent degradation. The core autophagic machinery, consists of ~30 proteins that are highly conserved from yeast to humans and most were originally identified in yeast (Feng et al., 2014) (Table 10.2). These proteins can be further divided into four modules, each of which have a specific function relating to the autophagic process: (1) the ULK1/ULK2 (unc51-like kinase complex); (2) The class III phosphatidylinositol 3′-kinase complex; (3) The Atg9 system; and

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(4) two ubiquitin-like conjugation systems including the LC3 (microtubule-associated protein light chain 3)/GABARAP (γ-aminobutyric acid associated) protein families (Feng et al., 2014; Mizushima et al., 2011) (Table 10.2).

Regulation of Autophagy in Yeast and Mammals At its most upstream level, nutrient deprivation–mediated autophagy is controlled by the TOR family of kinases, PI3-like kinases that monitor nutrient availability. In budding yeast under growth conditions replete with nutrients, TORC1 (target of rapamycin complex 1) signaling is high and represses autophagy by maintaining key autophagy proteins, such as Atg13, in a hyperphosphorylated state (Kamada et al., 2010). Similarly, in higher eukaryotes mTORC1 can phosphorylate and inhibit both ULK1 and Atg13 (Hosokawa et al., 2009). Under these conditions, yeast Atg13 has lower binding affinity to its partner, Atg1. Under conditions of nutritional stress, TORC1 activity is downregulated, allowing for the formation of the Atg13-Atg1 complex resulting in the stimulation of kinase activity of Atg1 (Kamada et al., 2010). This exact model however is under debate, as recent data have suggested that Atg13 is in a constitutive complex with Atg1 in yeast, analogous to what has been observed in higher eukaryotes (Kraft et al., 2012). In budding yeast, Atg1ULK1/ULK2 is a central autophagy kinase, which requires Atg13 and a stable ternary complex of Atg17-Atg31-Atg29 binding for its full activation. Atg1 drives autophagy induction by phosphorylating and activating other autophagy-related proteins, such as Atg9 (Papinski et al., 2014). Atg9 is a transmembrane protein that cycles between the PAS and other peripheral locations and aids in autophagosomal maturation by transferring membrane to the developing autophagsome (Orsi et al., 2012; Reggiori et al., 2004). The substrates of Atg1 in mammals are yet to be defined. Additional control of autophagy occurs at the level of autophagosome formation, which requires two evolutionarily conserved ubiquitin-like conjugation systems, Atg8 (LC3 in mammals) and Atg12 (ATG12) (Table 10.2). Atg8 and Atg12 are conjugated to their respective substrates, PE (phosphatidyl ethanolamine) and Atg5 via a mechanism similar to that of ubiquitin conjugation, in that dedicated E1-like activators, E2-like conjugation machinery, and E3-like ligases are all required (Ichimura et al., 2000). In the case of Atg8 a C-terminal glycine residue is first exposed by the action of the protease Atg4, which facilitates its conjugation onto PE by Atg7 (E1-like) and Atg3 (E2-like) (Ichimura et al., 2000). Atg8-PE formation is absolutely required for autophagosome formation and maturation by promoting membrane tethering and fusion between precursor autophagosomes (Nakatogawa et al., 2007). As with Atg8, Atg12 is conjugated with Atg5 via the same E1- and E2-like enzymes, Atg7 and Atg10, respectively. The formation of the Atg5-Atg12 conjugate has been shown to promote the activity of Atg3, thereby promoting the Atg8-PE reaction (Hanada et al., 2007). Although similar mechanisms exist in higher eukaryotes, there are seven Atg8 family members (MAP1LC3A, B/B2 & C, and GABARAP, L1, & L2) that are expressed broadly in various tissues, suggesting complex diversification of their function. A detailed pathway of activation for each Atg8 paralog has not yet been ascertained. Membrane phosphorylation is essential in generating precursor molecules for autophagosome formation. In particular, phosphatidylinositol 3-phosphate (PI3P) is

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TABLE 10.2 Proteins Involved in Autophagy

Atg1/ULK complex

Yeast

Mammals

Function

Atg1

ULK1/2

Ser/Thr protein kinase, phosphorylates Atg9

Atg13

ATG13

Links Atg17 to Atg1, phosphorylated by TORC1

Atg17

FIP200 (functional homolog)

Scaffold protein, ternary complex with Atg29 and Atg31

–

Ternary complex with Atg17 and Atg31

Atg29

Atg9 and its cycling system

PtdIns3K complex

Atg8 Ubl conjugation system

Atg12 Ubl conjugation system

Phosphorylated by ULK1; scaffold for ULK1/2 and ATG13

Atg31

Ternary complex with Atg17 and Atg29

Atg11

Protein scaffold, links core autophagic machinery to autophagy receptors and recruits other proteins to the PAS

Atg2

ATG2

Interacts with Atg18

Atg9

ATG9A/B

Transmembrane protein, directs membrane to the phagophore

Atg18

WIPI1/2

PtdIns3P-binding protein

Vps34

PIK3C3/VPS34

PtdIns 3-kinase

Vps15

PIK3R4/VPS15

Ser/Thr protein kinase

Vps30/Atg6

BECN1

Component of PtdIns3K complex I and II

Atg14

ATG14

Component of PtdIns3K complex I

Atg8

LC3A/B/C, GABARAP, GABARAPL1/2

Ubiquitin-like protein (Ubl), conjugated to PE

Atg7

ATG7

E1-like enzyme

Atg3

ATG3

E2-like enzyme

Atg4

ATG4A/B/C/D

Deconjugating enzyme, cysteine proteinase

Atg12

ATG12

Ubl

Atg7

ATG7

E1-like enzyme

Atg10

ATG10

E2-like enzyme

Atg16

ATG16L1

Interacts with Atg5 and Atg12

Atg5

ATG5

Conjugated by Atg12

Adapted from Feng, Y., He, D., Yao, Z., et al. 2014. The machinery of macroautophagy. Cell Res. 24, 24–41.

generated by PI3 kinases and is essential for all forms of autophagy. In budding yeast, vacuolar protein sorting protein 34 (Vps34), which is conserved in mammals (hVps34), produces PI3P (Schu et al., 1993). In yeast, Vps34 complex 1 consisting of Atg14, Atg6, Vps15, and Vps34 controls autophagy (Burman and Ktistakis, 2010). A similar complex exists in mammalian cells comprising Atg14L, Beclin 1 (Atg6 homolog), hVps15, hVps34, UV

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radiation-resistant associated (UVRAG), and autophagy/Beclin 1 regulator 1 (AMBRA1) (Burman and Ktistakis, 2010). In addition to PI3 kinases, PI3 phosphatases regulate the balance of PI3 phosphate, thereby modulating the formation and size of autophagosomes. Together these four protein modules are essential for the induction of autophagy in all eukaryotes.

Selective Autophagy Starvation-induced macroautophagy is considered to be a nonselective pathway as the autophagic machinery does not distinguish among target proteins in the cytosol. In addition, macroautophagy occurs primarily in response to nutrient limitation. In contrast, selective autophagy can occur in nutrient-replete conditions. The first example of such a pathway was elucidated in budding yeast and is termed the cytoplasm-to-vacuole transport (CVT) pathway (Harding et al., 1995). Selective autophagy in budding yeast requires the scaffold protein Atg11, which is largely dispensable for macroautophagy and stimulates this process by the recruitment of other autophagy proteins to the PAS (Yorimitsu and Klionsky, 2005). Further selectivity in this pathway is achieved by the binding of socalled autophagy “receptor” proteins that bridge the cargo of interest (which can be specific proteins or organelles) to the PAS via Atg11 (Lynch-Day and Klionsky, 2010). In addition the binding of the receptors to the cargo promotes membrane curvature, which excludes bulk cytosolic portions thereby ensuring further selectivity in the cargo (Nath et al., 2014). Selective autophagy receptors can be divided into two categories: ubiquitin-dependent and ubiquitin-independent (Khaminets et al., 2015). Although the two subtypes differ in their target specificity, they both interact with Atg8/LC3 through a conserved motif known as an AIM/LIR (Atg8-interacting motif/LC3-interacting region), defined as a stretch of four amino acids with the consensus motif Trp/Phe/Tyr–x–x–Leu/Ile/Val (W/F/YxxL/I/V), although receptors may engage with the autophagic machinery using noncanonical regions as well (Khaminets et al., 2015). The prototypic selective autophagy pathway is the CVT of budding yeast, which transports biosynthetic enzymes such as aminopeptidase1 (Ape1), alpha-mannosidase 1 (Ams1), and Ape4 to the vacuole (Lynch-Day and Klionsky, 2010). This pathway occurs constitutively, under nutrient-replete conditions, and requires the receptor proteins Atg19 and Atg34 (Shintani and Klionsky, 2004; Watanabe et al., 2010). These proteins do not appear to have any homologs in mammals; however; similar functions may be carried out by the autophagy receptors p62 (SQSTM-1), OPTN, NBR1, etc. (Khaminets et al., 2015). There are numerous types of selective autophagy pathways, each with their own specific receptor protein but for the purposes of this review, we will focus our attention on three pathways that appear to play the most important roles in the DDR, notably mitophagy, pexophagy, and chaperone-mediated autophagy (CMA). Mitophagy Mitochondrial quality control is of fundamental importance to the health of the cell, as the presence of damaged or dysfunctional mitochondria is deleterious due to the accumulation of reactive oxygen species (ROS) (Green and Levine, 2014). Defective mitochondria can be removed by autophagic clearance in a process termed mitophagy (Green and Levine, 2014).

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In budding yeast, nutrient deprivation and prolonged growth in nonfermentable carbon sources promote mitophagy and require the receptor protein Atg32 (Kanki et al., 2009). Atg32 directly interacts with Atg11 and this interaction is promoted by phosphorylation on two sites within the protein by the Hog1 (MAPK) and casein kinase II kinases (Kanki et al., 2013). Mitophagy in mammalian cells requires the presence of at least three independent receptors, OPTN (optineurin), NDP52, and Tax1BP1, and can occur following mitochondrial depolarization (Lazarou et al., 2015). Control of mammalian mitophagy occurs by ubiquitination of the mitochondrial membrane proteins and it is stimulated by two enzymes, PINK1 (PTEN-induced putative kinase 1) and the E3 ubiquitin ligase PARKIN (Youle and Narendra, 2011). During mitophagy, PARKIN ubiquitinates target mitochondrial proteins and PINK1 phosphorylates ubiquitin on the surface of mitochondrial proteins (Heo et al., 2015). This, in turn, stimulates the landing of additional PARKIN molecules onto the surface of mitochondria and the further ubquitination of proteins, enhancing the recruitment of additional receptors OPTN, NDP52, and Tax1BP1 in a feedforward loop, thereby stimulating mitophagy (Heo et al., 2015). Pexophagy Peroxisomes are sites of β-oxidation of long-chain fatty acids, a process that produces ROS. Thus, control of superfluous peroxisomes is critical for cellular survival. As with other selective autophagy pathways, pexophagy requires receptor binding to core autophagy components. In budding yeast, Atg36 anchors peroxisomes to autophagosomes via Atg8, Atg11, and the peroxisomal protein Pex3 (Motley et al., 2012). Similar to mitophagy, the kinase Hrr25 directly phosphorylates Atg36 to promote pexophagy (Pfaffenwimmer et al., 2014). In mammalian cells, pexophagy requires the receptors p62 and Nbr1 (Khaminets et al., 2015). Interestingly, ATM phosphorylates the peroxisomal protein Pex5 directly at peroxisomes, which stimulates its ubiquitination and subsequent recruitment of p62 (Zhang et al., 2015). Chaperone-Mediated Autophagy Cytosolic proteins may also be targeted to the lysosome directly in a process that does not require the presence of autophagic vesicles. This process is termed CMA and occurs by the selective recognition of the target protein by a chaperone in the cytosol that then targets it to the lysosome for degradation (Cuervo and Wong, 2014). The main chaperone that carries out this function is the cytosolic chaperone Hsc70 (heat shock cognate protein 70), which recognizes cytosolic proteins though pentapeptide-binding motif (Cuervo and Wong, 2014). This motif consists of a glutamine (Q) residue at the beginning or end of the sequence; one of the two positively charged amino acids, lysine (K) or arginine (R); one of the four hydrophobic amino acids, phenylalanine (F), valine (V), leucine (L), or isoleucine (I); and one of the two negatively charged amino acids, glutamic acid (E), or aspartic acid (D) (Cuervo and Wong, 2014). Once proteins are recognized by Hsc70, they are translocated to the lysosome where they interact with the outer lysosomal protein LAMP2-A (lysosome-associated membrane protein type 2A). The protein is unfolded and threaded into the lysosome. CMA is a distinct pathway from other selective autophagy pathways in that it does not require any of the core components of the autophagy pathway and represents a selective autophagy-like machinery capable of delivering proteins to the lysosome (Cuervo and Wong, 2014).

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AUTOPHAGY AND DNA DAMAGE—A COMPLEX CROSS TALK The connections between autophagy and DNA damage were first elucidated by studies on the effect of autophagy on tumorigenesis. Pioneering work from the Levine lab established that autophagy could be tumor-suppressive in some contexts; by demonstrating that human breast cancer cell lines (MCF7) had mono-allelic deletions of the autophagy gene Beclin 1 (Atg6) (Liang et al., 1999). Indeed, expression of Beclin 1 in MCF7 cell lines reduced contact inhibition and decreased cellular proliferation (Liang et al., 1999). The observations on Beclin 1 were extended to other autophagy genes, such as UVRAG, which was isolated through its ability to complement the UV sensitivity of Xeroderma Pigmentosum cells (Liang et al., 2006). Under metabolic stress conditions, beclin 1 heterozygotes displayed increased generation of ROS, which caused DNA damage and aneuploidy (KarantzaWadsworth et al., 2007). Scavenging ROS by N-acetyl cysteine (NAC) decreased DNA damage in beclin 1 –/+ cells suggesting that ROS in the main cause of genomic instability in autophagy-deficient cells (Karantza-Wadsworth et al., 2007). Mitochondria and peroxisomes may link autophagy, ROS, and DNA damage, as these organelles are the main source of ROS in cells. This idea is borne out of observations that autophagy-deficient cells accumulate dysfunctional mitochondria and elevated ROS (Galluzzi et al., 2015). ROS may then cause genomic instability by directly damaging DNA resulting in DNA DSBs. In this way autophagy may act as a tumor-suppressive phenomenon by maintaining organellar homeostasis and genomic stability (Galluzzi et al., 2015). However, the exact role of autophagy in cancer is complex. On one hand, many cancer cell types are defective for autophagy but conversely, there are tumor types that display elevated autophagy and indeed depend on this elevated autophagy for survival (Galluzzi et al., 2015). For example, in a particularly malignant form of pancreatic cancer, pancreatic duoductal adenocarcinoma (PDAC), tumor cells display elevated autophagy and DNA damage (Yang et al., 2011). Therefore the autophagy status of a cell does not necessarily correlate with the amount of spontaneous damage present. One commonality seen in the autophagy-defective tumors was that the source of DNA damage in PDAC cells also appeared to be largely from ROS (Yang et al., 2011). These contradictory observations can be reconciled if one considers a two-step model for autophagy in tumor progression as recently proposed (Galluzzi et al., 2015) combined with a stochastic loss of other tumor-suppressive genes (Yang et al., 2014). In this model the transition to malignancy could involve a temporary loss of autophagy activity, which then promotes genomic instability as previously described. In addition, malignant cells may also stochastically lose other tumor suppressors, such as p53, which would result in cells blind to the presence of DNA damage and thus proliferate, despite the presence of unrepaired DNA, thereby amplifying genomic instability and increasing mutations. Then, as cells develop into mature tumors, autophagic activity is restored and indeed, in some cases could be increased relative to wild-type cells. Direct evidence for this model is, as of now, lacking but evidence showing the efficacy of autophagy suppression in tumor regression in mouse models engineered to randomly lose p53 activity suggest that this process may indeed occur (Yang et al., 2014). There are many numerous questions arising from these observations, the most fundamental of which is (1) How do the DDR and autophagy actually communicate which each

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other, at a molecular level? As of yet, there have been many correlative descriptions of cross talk but direct evidence of this phenomenon is lacking. (2) How does the autophagy status of cells affect their ability to response to DNA damage?

A DNA Damage–Induced Autophagy Pathway A variety of different DNA-damaging agents have been shown to induce autophagy. Shimizu et al. demonstrated this in mouse embryonic fibroblasts (MEFs) lacking the proapoptotic genes Bax and Bak (Shimizu et al., 2004). Bax−/− Bak−/− MEFs treated with the DNA-damaging agents etoposide or staurosporine displayed autophagy upregulation and underwent a nonapoptotic cell death that was dependent on autophagy (Shimizu et al., 2004). Subsequent work by many laboratories has established how genotoxic stress induces autophagy in higher eukaryotes. At its core, GenoToxin stress–induced Autophagy (henceforth referred to as GTA), requires the ATM-p53-mTOR signaling axis (see Fig. 10.1 for entire pathway). After genotoxic stress, p53 is activated in an ATM/ATR-dependent manner and binds to the promoters of numerous autophagy genes, such as ULK1/ULK2, ATG7, ATG4A, and UVRAG, and mediates their transcriptional upregulation (Kenzelmann Broz et al., 2013). This transcriptional upregulation is important for GTA as p53−/− cells are unable to induce autophagy after DNA damage (Kenzelmann Broz et al., 2013). p53 may also mediate a specific DNA damage responsive branch of the autophagy pathway through upregulation of the lysosomal protein DRAM1 (damage-regulated modulator of autophagy-1), which to date appears to be the only unique protein connecting DNA damage to the autophagy pathway (Crighton et al., 2006). However, it is not clear whether DRAM1 has roles in autophagy that is mediated by other cues, such as nutrient deprivation. Indeed, DRAM1 has also been shown to be involved in other autophagic processes, such as xenophagy—the selective destruction of pathogens by the autophagic machinery (van der Vaart et al., 2014). In addition, the DRAM1 locus encodes multiple p53-inducible splice variants, and interestingly, these proteins do not localize lysosomes but instead appear to be at peroxisomes and ER (Mah et al., 2012). These observations suggest that p53 may control specific types of autophagy in addition to bulk autophagy (Mah et al., 2012). Another mechanism by which p53 can activate autophagy is via the activation of the protein death associated protein kinase-1 (DAPK1) (Martoriati et al., 2005). DAPK1 promotes autophagy in two ways: (1) inhibition of the antiautophagic factor MAP1B (microtubuleassociated protein 1b) which inhibits LC3 (Harrison et al., 2008) and (2) by phosphorylation of Beclin 1 (Zalckvar et al., 2009). A closely related p53 protein, p73, can also induce autophagy in a p53-independent manner by transcriptional upregulation of autophagy genes (Crighton et al., 2007; He et al., 2013). In addition to activating p53, ATM may also promote autophagy through inhibition of mTOR signaling (Alexander et al., 2010). This is achieved by ATM-mediated phosphorylation of the serine/threonine kinase Lkb1 that activates the AMP kinase, that, in turn, inhibits mTORC1 via its regulator Tsc2 (Alexander et al., 2010). In addition, recruitment and activation of the DNA repair enzyme PARP-1 to the sites of DNA damage consumes NAD+ molecules, which can also sensed by AMPK and increases its activity toward mTORC1 (Rodriguez-Vargas et al., 2012). With regards to ATM, this response appears largely specific

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FIGURE 10.1 Pathways of GTA. Autophagy-related proteins are depicted in green, DNA damage response proteins in red, and energy-sensing proteins in blue. GTA is promoted by ATM/ATR signaling (see text for details) and 2 transcriptional modules mediated by p53 and p73 upregulate various autophagy genes after genotoxic stress. Note that the genes indicated are only a representative subset of all autophagy genes upregulated after genotoxic stress. p53 also promotes autophagy by activation of DAPK1. GTA may also be stimulated by ATM/ATR impinging on mTOR signaling by the activation of AMPK1. ATM/ATR may also promote chaperone-mediated autophagy, leading to the selective destruction of Chk1. Data from budding yeast suggest that Securin and Rnr-1 may also be targets of autophagy. Finally, high amounts of DNA damage may inhibit selective autophagy of the transcription factor GATA4 by p62, thereby promoting senescence onset. Inset box: Roles of ATM in selective autophagy. ATM promotes pexophagy in response to ROS stress and may promote mitophagy (see text for details). GTA, genotoxininduced autophagy; ROS, reactive oxygen species.

to ROS and requires a cytoplasmic pool of ATM. Moreover, mTOR downregulation was not observed in response to other damaging agents such as etoposide (Alexander et al., 2010). Therefore the exact role of mTOR signaling in GTA remains enigmatic. It is not yet clear which pathway of autophagy genotoxins induces, i.e., whether they are selective or bulk autophagy pathways. A recent report has demonstrated that many diverse genotoxins can induce CMA in mouse fibroblasts (Park et al., 2015). Recently, data from budding yeast suggest that endonuclease-induced DSBs and genotoxins induce a largely selective autophagy pathway, as judged by the requirement for Atg11 and absence

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of starvation-induced macroautophagy measured by alkaline phosphatase activity (Eapen et al., manuscript in preparation; Dotiwala et al., 2013). In addition, in budding yeast, the requirement for DDR proteins appears to be largely specific for GTA, which is in contrast to the roles of such proteins in higher eukaryotes. GTA in yeast requires the action of ATM, ATR, and CHK2 kinases. Most notably, these kinases are not required for autophagy induction after rapamycin treatment, suggesting that GTA in yeast is distinct from nutrient deprivation–induced autophagy. In agreement to what has been observed in mammalian cells, GTA in yeast also requires transcriptional upregulation of numerous autophagy genes. This stimulation of transcriptional activity occurs via negative regulation of the transcriptional regulator Rph1 (KDM4 in mammals) by CHK2. Although yeast GTA is a selective autophagy pathway, none of the known autophagy receptor proteins are required nor is any canonical selective autophagy pathway triggered. This suggests that GTA is a unique autophagy pathway, which degrades specific substrates and requires its own machinery (Eapen et al., manuscript in preparation).

ATM—A Diverse Kinase With Roles Outside of the Nucleus Recent reports have identified ATM as a key regulator of selective organelle autophagy (Fig. 10.1, inset box). ATM is abundant in various subcellular locations such as the mitochondria and peroxisomes (Zhang et al., 2015). ATM is activated by peroxisomal and mitochondrial stress in a manner distinct from genotoxic stress and initiates a noncanonical ATM-mediated autophagy pathway (Zhang et al., 2015). ATM can directly interact with the peroxisome protein Pex5 and mutations in this binding affects the peroxisomal functions of ATM, but not its role in the DDR. Specifically during pexophagy, ATM phosphorylates and activates the peroxisome protein Pex5 on Serine 141 at peroxisomes (Zhang et al., 2015). This promotes ubiquitination of Pex5 and subsequent recognition by p62 via its ubiquitinbinding domain. Further activation of autophagy can occur by ATM-mediated repression of mTORC1 at peroxisomes (Zhang et al., 2015). ATM may also be involved in mitophagy as ATM−/− mice display increased mitochondrial loads, ROS, and oxygen consumption; however, direct evidence of this cross talk is lacking (Valentin-Vega et al., 2012).

Autophagy and Senescence In response to oncogenic insults, such as very high amounts of DNA damage or the hyperactivation of oncogenes, cells undergo permanent arrest in a process known as senescence (Campisi, 2000). Cellular senescence is marked by the irreversible arrest of cell proliferation and is considered to be a tumor-suppressive pathway (Campisi, 2000). In this context, it has been demonstrated that the DDR may inhibit autophagy, at least transiently, in order to induce cellular senescence (Kang et al., 2015). Cellular senescence results in widespread changes in metabolism, of which one such example is the senescence-associated secretory phenotype (SASP). The SASP is a hallmark of senescent cells and results in the secretion of proinflammatory signals such as cytokines, chemokines, and interleukins (Campisi, 2000). Until recently, it was not clear how the SASP was regulated, since SASP induction does not require the canonical senescence regulators p53 or p16. A recent report from the Elledge group has identified the

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transcription factor GATA4, and its regulation by selective autophagy, as a key positive controller of the SASP. Under normal growth, GATA4 is degraded by p62-mediated selective autophagy. Upon the induction of senescence, p62-mediated degradation of GATA4 is inhibited, resulting the stabilization of GATA4, and the transcriptional upregulation of genes required for the establishment of the SASP (Kang et al., 2015). Interestingly, this inhibition appears to be mediated by the ATM/ATR kinases, as inhibition of ATM and ATR prevented the autophagic degradation of GATA4 by p62 (Kang et al., 2015). These results suggest that autophagy must be downregulated to establish senescence, which is in contrast to other reports demonstrating that autophagy is required for the establishment of senescence (Young et al., 2009). As with cancer, the role of autophagy in senescence is complex, with evidence of autophagy having both positive and negative roles in senescence. Similar to cancer, these conflicted ideas can be resolved with a two-step model for autophagy in senescence establishment. During senescence establishment, selective autophagy of pro-senescent factors may be transiently inhibited and subsequently, general autophagy is reestablished to further promote senescence. This idea has support from the observation that transient inhibition of autophagy alone was sufficient to result in an increase of senescence cells (Kang et al., 2015). Taken together, the establishment of senescence appears to be a unique situation in which the DDR inhibits, rather than promotes, autophagy. This may occur, in part, due to the nature of the stimulus. For example if DNA damage is above a threshold, senescence will result. Additionally, while the DDR may generally promote autophagy, specific selective autophagy of certain substrates may be downregulated, either due to modifications on the autophagic machinery or on the cargo proteins themselves. Further work in this area should clarify which mechanisms are at play here.

Autophagy Regulation of the DDR One way by which autophagy controls the DDR is by controlling the levels of various proteins involved in the detection and repair of damaged DNA. In budding yeast, and in higher eukaryotes, autophagy has been shown to control the levels of various checkpoint proteins such as Pds1 (Securin) and Chk1 (Dotiwala et al., 2013; Park et al., 2015). Hyperactivation of an Atg11-dependent pathway in yeast causes mislocalization and degradation of Pds1, resulting in permanent arrest of cells after DNA damage due to the nuclear exclusion of Esp1 (separase). These results suggest that GTA targets mitotic promoting factors to enforce cell cycle arrest (Dotiwala et al., 2013). Alternatively, autophagy has been shown to also target positive regulators of the checkpoint, most notably Chk1, but conflicting reports have emerged regarding this point. Working in mouse fibroblasts, the Cuervo lab has demonstrated that LAMP2A−/− cells, which are defective for CMA, accumulate elevated levels of both total and phosphorylated Chk1 (Park et al., 2015). We remind the readers that CMA does require the canonical autophagy machinery. The effects were not seen in Atg7−/− cells suggesting that, in this case, macroautophagy was not involved in Chk1 stability. However, Ryan’s group demonstrated that both total and phosphorylated Chk1 levels are reduced in Atg7−/− MEFs (Liu et al., 2015). This reduction occurs due to elevated proteasome activity, leading to enhanced degradation of Chk1—suggesting that Chk1 is not normally degraded by lysosomal activity. The

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reasons for this discrepancy are not immediately obvious as both studies employed similar DNA-damaging agents and cell lines. A consequence of reduced Chk1 levels in these MEFs was a decrease in HR which resulted in Atg7−/− cells becoming hyperreliant on the nonhomologous end joining pathway to repair DNA damage (Liu et al., 2015). A similar result was observed in autophagy-defective cells from human nasopharyngeal carcinoma which also have lower levels of Rad51 thereby resulting in defective recombinational repair (Mo et al., 2014). A recent study has demonstrated that autophagy-defective MEFs are also defective in NER. Specifically, Atg5−/− MEFs display impaired repair of UV-induced cyclobutane pyrimidine dimers (CPD) and 6–4 photoproducts (6–4 P) (Qiang et al., 2015) due to the stabilization of the transcription factor TWIST1. TWIST1 has previously been shown to be an autophagy target recognized by the p62 autophagy receptor and negatively regulates the expression of the NER repair enzymes XPD and DDB2 (Qiang et al., 2015). The connection between GTA and DNA repair has also been elucidated from studies in budding yeast. Treatment of yeast cells with the alkylating agent methyl methane sulfonate (MMS) results in autophagy-mediated degradation of the enzyme ribonucleotide reductase 1(Rnr1) (Dyavaiah et al., 2011). Rnr1 in concert with other Rnr proteins (Rnr2, 3, 4) generates deoxyribonucleotides (dNTPs) from ribonucleotide precursors and therefore is essential for any form of DNA repair and requires de novo DNA synthesis. Elevated dNTPs in cells have been shown to result in increased mutation rate, therefore control of dNTP production by GTA may control mutagenesis (Dyavaiah et al., 2011). GTA may also control proteins involved in the repair of DNA breaks, such as Sae2 and Exo1 (Robert et al., 2011). Treatment of cells with valproic acid, a histone deactelyase inhibitor resulted in autophagy-mediated destruction of these enzymes, leading to defects in HR repair. However, in contrast to this study, recent reports have suggested that Sae2 is a highly unstable enzyme and appears to be under proteasomal and not autophagy control (Tsabar et al., 2015). Hyperactivation of autophagy using other methods, such as rapamycin treatment, or expression of dominant-active autophagy genes, did not alter the stability of Sae2 (Tsabar et al., 2015). In addition, yeast cells defective for autophagy do not appear to be sensitive to most genotoxic agents and are proficient for both NHEJ and recombinational repair (Eapen and Haber, unpublished).

CONCLUSIONS AND PERSPECTIVES Autophagy has now come to be recognized as an important pathway for its roles in human health in relation to cancer, immunity and aging. In particular, autophagy-mediated control of enzymes involved in genomic integrity plays a critical role in cellular response to DNA damage. The communication between these pathways is particularly relevant to cancer as the progression to malignancy often involves, or results in aberrant DNA damage and/or autophagy signaling. Defective autophagy leads to the accumulation of potentially toxic intermediates, such as misfolded proteins or damaged organelles, which are sources of DNA damage. Likewise, DNA damage signaling has also been shown to stimulate autophagy via the core DDR machinery.

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Genotoxin-induced autophagy (GTA) controls the levels of various DNA repair and cell cycle enzymes and in some instances, is required for the accurate repair and detection of damaged DNA. In contrast, extensive DNA damage may inhibit selective autophagy of target proteins to promote senescence. Taken together, these results lead us to propose a two-phase model as seen in Fig. 10.2. DNA damage, from a variety of sources, leads to cell cycle arrest. Depending on the amount and extent of damage, cells can either undergo irreversible cell cycle arrest (senescence) or a transient arrest leading to the resolution of the damaged DNA and the resumption of cell cycle progression. In the former case, extensive DNA damage may inhibit autophagy, at least transiently, to promote senescence onset, whereas in the latter, DNA damage stimulates autophagy, to promote repair and checkpoint arrest. Another difference between these models is the timing of these responses; GTA occurs relatively quickly, within hours, whereas autophagy inhibition leading to senescence would occur in the span of days. In either case the initial early events will be the same, in that GTA will be induced. DNA damage regulation of autophagy can be considered to be tumor suppressive and is critical for the cellular response to DNA damage. Moving forward, there are numerous questions that remain to be addressed by the field.

DNA damage Cell cycle arrest ATM/ATR & p53

Repair and recovery

Senescence

Promote repair Enforce arrest

Arrest/apotosis

Checkpoint activation Magnitude of autophagy flux

Senescence

Hours

Days

FIGURE 10.2 Unified model for the role of autophagy in the DNA damage response. Depending on the amount and extent of DNA damage, ATM/ATR signaling may either promote or inhibit autophagy. Below a threshold amount of DNA damage autophagy is induced and promotes cell cycle arrest and the repair of damaged DNA as denoted by Red line, whereas damage above the same threshold transiently inhibits selective autophagy as denoted by Blue Line, to promote senescence (see text for additional details).

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Which molecules mediate the communication between the DNA damage and autophagy pathways? Although core principles have emerged from studies of GTA in mammalian and yeast systems, no protein unique to this pathway has been defined. Recently, using budding yeast we have performed a genomewide screen for both positive and negative regulators of GTA and have discovered ~10 genes whose mutation affects GTA. These proteins belong to diverse classes on enzymes ranging from MAP kinases, phosphatases, and membrane-associated proteins (Eapen et al., manuscript in preparation). Whether similarly conserved proteins play the same roles in mammalian systems will be an interesting question to address.

l

Which pathway of autophagy is involved? From studies in budding yeast, GTA appears to be a largely selective autophagy pathway, however, none of the canonical autophagy receptors appear to be involved and no selective autophagy pathway appears to be triggered (Eapen et al., manuscript in preparation). Hence, at least in budding yeast, GTA is a unique pathway that is distinct from canonical selective autophagy pathways. In mammalians, GTA can stimulate CMA, which represents an autophagy pathway similar to selective autophagy, but does not depend on any apparent receptor (Park et al., 2015).

l

What are the physiological roles of GTA? This appears to be best-addressed question of all posed in this field. Autophagydefective cells, ranging from yeast to mammals, are defective for various forms of DNA repair and cell cycle progression. Nevertheless, there may be differential outcomes of GTA depending on the amount or type of DNA damage that is inflicted (Fig. 10.2).

l

What are the substrates of GTA? As of now only a handful of substrates are known to be targets of GTA (Fig. 10.1). Identification of additional targets will aid our understanding of the physiological role that GTA may play, and in this regard, techniques for autophagosomal profiling in yeast and mammals should prove to be useful.

l

The use of comparatively simpler model organisms, such as budding yeast, may prove to be highly beneficial to answer these questions, due to the availability of welldefined DNA repair assays and the ability to quickly perform genomewide screens. Nevertheless, with the advent of CRISPR technology, such assays may become a commonplace in mammalian systems as well and is sure to deepen our understanding of the cross talk between DNA damage and autophagy.

Acknowledgments VVE was a HHMI International predoctoral fellow (2013–15). DW and BL are Trainees of NIH Genetics Training Grant TM32 GM007122. Work in the Haber lab has been supported by NIH grants GM20056 and GM61766. We sincerely apologize to all the authors whose works we were not able to cite due to space restrictions.

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11 Autophagy and Cancer Yoshitaka Isaka, Tomonori Kimura, Yoshitsugu Takabatake and Atsushi Takahashi O U T L I N E Introduction 237 Cancer-Promoting Action of Autophagy 238

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Autophagy is a homeostatic cellular degradation pathway for scavenging damaged or unnecessary cellular organelles and proteins. Although autophagy is originally regarded as a tumor-suppressive factor, cancers employ autophagy to survive under metabolic stresses. At present, a number of clinical trials are revealing the promising role of autophagy modulator as a novel anticancer therapy. Although anticancer drugs, for example, cisplatin, frequently induce acute kidney injury (AKI), autophagy plays a protective role against AKI. Combination therapy of chloroquine with anticancer drugs may augment the therapeutic effect on cancer, but could exacerbate AKI. Here, we review the close relationship between autophagy and cancer, especially focusing on two conflicting, cancer-promoting and cancer-suppressing, roles of autophagy in cancer cell, and address the autophagy modulating therapy for cancer.

INTRODUCTION Autophagy maintains intracellular homeostasis to degrade and recycle protein aggregates or damaged organelles (Klionsky and Emr, 2000; Mizushima and Komatsu, 2011). Degraded protein or organelles are followed by generating amino acids, sugars, fatty M.A. Hayat (ed): Autophagy, Volume 11. DOI: http://dx.doi.org/10.1016/B978-0-12-805420-8.00011-1

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acids, and nucleosides to be recycled for macromolecular synthesis and energy production (Mizushima and Komatsu, 2011, Rabinowitz and White, 2010). Autophagic activity is regulated by several factors, including nutrient-related mechanistic target of rapamycin (mTOR), energy-related AMP-activated protein kinase, and hypoxia-inducible factor (HIF). When activated, orchestrated autophagy-related protein complexes form double-membrane vesicle to engulf the cytoplasmic proteins and organelles. Autophagy also cooperates with ubiquitin–proteasome system by recognizing p62 to degrade within autophagosome (Komatsu et al., 2007). Although autophagy works at low basal levels to maintain cellular homeostasis, this system is particularly important under starvation. Furthermore, it is activated during metabolic stress (Rabinowitz and White, 2010). Autophagy is originally regarded as a tumor-suppressive factor, because allelic loss of autophagy-related gene, such as Beclin 1, was observed in human cancers (Aita et al., 1999). On the contrary, autophagy is activated in cancers to survive under metabolic stress and might provide resistance to anticancer therapy (Apel et al., 2008; Degenhardt et al., 2006). Here, we review the close relationship between autophagy and cancer, especially focusing on two conflicting, cancer-promoting and cancer-suppressing, roles of autophagy in cancer cell, and address the autophagy modulating therapy for cancer.

CANCER-PROMOTING ACTION OF AUTOPHAGY Autophagy can provide an energy source to survive under the unfavorable environment in normal cells, and similar cell-surviving system is applied to cancer cells. Although cancer cells are exposed to increased metabolic stress due to nutrition deficiency and hypoxia as a result of poor angiogenesis, they can survive under a hypoxic and acidic condition in spite of the lack of mature vessels. For adenosine triphosphate (ATP) production, they mainly employ glycolysis pathway (the Warburg effect), which is less effective than TCA pathway, and therefore, cancer cells require more glucose uptake than normal cells (Vander Heiden et al., 2010). In addition to this inefficient energy production, they need to correspond to high-energy demand for cell proliferation. Autophagy is assumed to provide alternative energy supply for cancer cells under such unfavorable conditions. In fact, autophagy in tumors is observed exclusively in unvascularized, metabolic-stressed region (Degenhardt et al., 2006). Some tumor cell lines exhibited highly increased autophagic activities under fed conditions, suggesting that inherent metabolic stresses drive the autophagy in cancer cells. Although extensive metabolic stress initiates apoptosis by triggering caspase activation (Harris, 2002), autophagy supports tumor cell survival by providing nutrients or scavenging toxic cellular wastes. Thus, inhibiting autophagy may suppress the tumor progression to accelerate apoptosis under metabolic stress (Mathew et al., 2007a). This mechanism might function especially in the initiation stage of tumor growth where tumor is deficient in blood supply. Nutrient deficiency can be sensitized and be controlled by the PI3K/Akt/ mTOR pathway, major checkpoint in regulating autophagy, in cancer cells. This pathway manages the growth, proliferation, and nutrient obtainability (Wullschleger et al., 2006). The increased activity of this system results in high metabolic action associated with biosynthesis procedures such as DNA, protein, and lipid synthesis for cell proliferation during tumor progression.

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Several mechanisms to overwhelm the metabolic stress during cancer progression have been suggested (Fig. 11.1A). Hypoxia-induced autophagy is mediated through BNIP3 and BNIP3L induced by HIF (Bellot et al., 2009). Under hypoxic conditions, BNIP3 gene expression is induced through HIF-1 binding to the responsive element in the BNIP3 promoter (Bruick, 2000). Thereafter, hypoxia-induced BNIP3 dimerizes and integrates into the outer (A)

(B)

FIGURE 11.1 (A) Process of autophagy, regulating factor, and autophagic modulation. Autophagy is suppressed by nutrient-dependent mTOR, and activated by stress, AMPK, and HIF, which are increased in cancer cells. Autophagy deficiency and oxidative stress activate Nrf2, which promotes tumor survival. Several dugs can inhibit autophagy and might augment the effect of chemotherapy. (B) Effect of combined therapy with anticancer and autophagy-suppressing drugs. Combined therapy increases the sensitivity to chemotherapy and promotes the cancer cell death. On the other hand, combined therapy increases the risk of acute kidney injury. mTOR, mechanistic target of rapamycin; AMPK, AMP-activated protein kinase; HIF, hypoxia-inducible factor; Nrf2, nuclear factor (erythroid-derived 2)-like 2.

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mitochondrial membrane, which acts as a mediator of mitochondrial autophagy, a survival adaptation to control reactive oxygen species (ROS) production and DNA damage (Kim et al., 2002). However, in many cancers, BNIP3 expression and mitophagy are significantly less affected by hypoxia. Similar mechanisms, beneficial to organisms adapted to stressful environments, may also confer malignant cells with survival features (Band et al., 2009). Autophagy is important to remove damaged protein and organelles, especially mitochondria. Autophagy serves not only to provide substrate to mitochondria but also to preserve mitochondrial pool by removing defective ones. These autophagic actions are critical for maintaining metabolism and survival (Guo et al., 2013). ROS production and DNA damage trigger the activation of p53, a key checkpoint cell cycle regulator and tumorigenesis. Autophagy may degrade p53 and limit its accumulation, thereby suppresses the p53 response, such as DNA damage, oxidative stress, or other aspects of oncogene activation (Korolchuk et al., 2009). p53 also regulates the pathways involved in glucose metabolism, where p53 inhibit the shift to glycolysis characteristically seen in cancers (Cheung and Vousden, 2010). Thus, autophagy may play a cancer-promoting role.

CANCER-SUPPRESSING ACTION OF AUTOPHAGY Originally, autophagy was shown to work in a cancer-suppressing fashion. The heterozygous disturbance of Beclin 1, an autophagy-related gene, displays higher occurrence of spontaneous tumors (lymphomas, leukemias, hepatocellular carcinomas, and lung adenocarcinomas) (Qu et al., 2003; Yue et al., 2003). Monoallelic loss of Beclin 1 gene was observed in 40–75% of human prostate, breast, and ovarian cancer (Aita et al., 1999; Liang et al., 1999). However, liver-specific Atg7-deficient mice or mice with systemic mosaic deletion of Atg5 showed benign liver adenoma, but no malignant formation (Inami et al., 2011, Takamura et al., 2011). Beclin 1 was considered as a tumor-suppressor gene, but it is located adjacent to breast and ovarian tumor suppressor breast cancer 1, early onset, BRCA1, on chromosome 17q21. Recently, it was reported that breast and ovarian cancer results from missense mutations in BRCA1 regardless of whether Beclin 1 gene was deleted or not (Laddha et al., 2014). In addition, large-scale genomic analysis of human cancers did not ascertain frequent mutations in Beclin 1 or other essential autophagy gene (Lawrence et al., 2014; Vogelstein et al., 2013). Thus, Beclin 1 gene is not regarded as a tumor-suppressing gene in most human cancer, including breast, ovarian, and prostate cancer (Laddha et al., 2014). As autophagy-deficient mice exhibited benign liver tumor, autophagy may be important to suppress tumor instigation in liver. p62, accumulated in autophagy-deficient liver as specific substrate of autophagy, may be critical for tumor promotion (Komatsu et al., 2007). p62 binds to Kelch-like ECH-associated protein 1 (KEAP1) and continues to activate nuclear factor (erythroid-derived 2)-like 2 (Nrf2), which is a master regulator of the antioxidant defense response, but promotes cancer cell survival. Therefore, autophagy-deficient mice exhibited the accumulation of p62, inhibition of KEAP1, and Nrf2 activation, resulting in cancer cell growth and survival. Autophagy deficiency induces oxidative stress, activation of the DNA damage, and genomic instability, which causes tumor initiation and progression (Karantza-Wadsworth et al., 2007; Mathew et al., 2007b). Increased oxidative stress further activates Nrf2, which leads to tumor growth. Clear cell renal cell carcinoma is often linked

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to gain of chromosome 5q, which leads to overproduction of p62, promoting resistance to redox stress and tumor growth (Li et al., 2013). In addition, p62 is necessary for Ras to trigger IκB kinase through the polyubiquitination of tumor necrosis factor receptor-associated factor 6, and p62-deficient mice are resistant to Ras-induced lung adenocarcinomas (Duran et al., 2008). Autophagy is also necessary to explicate the antiimmune response. In response to chemotherapy, autophagy in dying cancer cells enables to release ATP, which attracts immune cells and triggers antiimmune response (Michaud et al., 2011). Autophagy deficiency might stimulate necrotic cell death or inflammation, leading to nonautonomous tumor promotion through chronic inflammatory response (Degenhardt et al., 2006). As seen here, autophagy seems to have different effects on the different stages of cancer, especially in the initiation stage. We, however, observed no tumor formation even in old proximal tubular specific Atg5-null mice (Kimura et al., 2011), suggesting that effect of autophagy deficiency on tumor formation may be different in tissue. Further studies are necessary to understand the precise role of autophagy on cancer.

AUTOPHAGY-SUPPRESSING DRUG As reviewed above, autophagy is assumed to provide alternative energy supply and remove toxic substrates under metabolic stresses in cancer cells. Thus, autophagy-suppressing drug might act as anticancer therapy (Fig. 11.1A). Autophagy-suppressing chloroquine and hydroxychloroquine are used as anticancer drug, although the precise mechanism is yet unclear. Accumulating evidences have shown that chloroquine and hydroxychloroquine drive cancer cells sensitive to radiation or other anticancer drugs. A number of clinical trials are now in process and, as far as judging from the available results, this drug may change the strategy of cancer therapy (Amaravadi et al., 2011). Chloroquine and hydroxychloroquine have long been used to treat or prevent malaria. Chloroquine is also used to treat auto-immune diseases due to its characteristic to suppress immune systems. Although the exact mechanism how they exhibits antimalarial effect remains unknown, chloroquine has been employed to arrest autophagic clearance through the weak-base lysosome-tropic features (Homewood et al., 1972). When chloroquine enters lysosome, chloroquine becomes protonated due to low pH within lysosome, and accumulated protonated-form of chloroquine let the lysosomal fluid less acidic. Thus, chloroquine is used as antiautophagy drug by decreasing lysosomal function. Chloroquine and hydroxychloroquine were examined in human cancer cell lines and animal models. They augmented the anticancer activity of cyclophosphamide by inhibiting autophagy in Myc-driven lymphoma (Amaravadi et al., 2007; Maclean et al., 2008). Chloroquine also increased cell death in imatinib-resistant BCR-ABL-positive CML cell lines and enhanced the effect of the HDAC inhibitor (Bellodi et al., 2009; Carew et al., 2007). In addition to chloroquine and its analog, various autophagy inhibitors, such as bafilomycin A1, 3-methyladenine, and pepstain A, have been studied as antitumor drugs. These drugs, including chloroquine and its derivatives, are not specific modulators of autophagy activity. More specific inhibitor of autophagy is superior approach in cancer therapy and is now under investigation (Cheong et al., 2012).

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AUTOPHAGY-SUPPRESSING DRUG AND ACUTE KIDNEY INJURY In kidney, the important role of autophagy has been shown in proximal tubular cells, the main target of chemotherapy-induced acute kidney injury (AKI). Proximal tubules-specific autophagy-deficient mice showed severe AKI against ischemia-reperfusion injury compared with wild-type mice (Kimura et al., 2011), indicating that autophagy plays a critical role in protecting proximal tubular cells against AKI (Isaka et al., 2012). In addition, cisplatin treatment also induced serious injury in proximal tubule–specific autophagy-deficient mice (Kimura et al., 2011; Takahashi et al., 2012). Recently, quite similar findings were also reported (Liu et al., 2012), and these data demonstrated that autophagy plays a protective role in kidney proximal tubular cells against AKI. Treatment with chloroquine combined with anticancer reagents may exert an additional effect in cancer treatment (Rabinowitz and White, 2010; Sasaki et al., 2010). Without chloroquine cancer cells activates autophagy to resist anticancer drug. Inhibiting autophagy by chloroquine may sensitize not only cancer cells but also normal organs to chemotherapy. Chemotherapy can induce a variety of acute and chronic organ injury. Proximal tubules are one of the most susceptible cells to chemotherapeutic agents because many chemotherapeutic agents and their metabolites are excreted through proximal tubular epithelial cells (de Jonge and Verweij, 2006). Therefore, anticancer drugs are sometimes restricted by their nephrotoxic side effects. AKI also causes unfavorable complications with poorer prognosis (Mehta et al., 2007). Thus, combined chemotherapy with chloroquine may augment chemotherapy-induced AKI (Fig. 11.1B).

CONCLUSION Autophagy was originally shown to work in a cancer-suppressing fashion, because the heterozygous disturbance of Beclin 1 displays higher occurrence of spontaneous tumors. Although autophagy-deficient mice exhibited benign tumor partly due to p62 accumulation, large-scale genomic analysis of human cancers did not ascertain frequent mutations in essential autophagy gene. On the other hand, autophagy is assumed to provide alternative energy or nutrient supply for cancer cells under unfavorable conditions. Thus, autophagysuppressing drug might act as cancer therapy. Chloroquine is one of the promising drugs in the field of cancer therapy and relatively guaranteed for its safety use, especially for the usage of short period. However, unexpected AKI might occur especially under the combinational usage with anticancer drug, possibly through the inhibition of autophagy. Therefore, oncologist need to be aware of this possible effect.

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12 ULK1 Can Suppress or Promote Tumor Growth Under Different Conditions Tian Mao and Ouyang Liang O U T L I N E Introduction 246

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The Serine/Threonine Protein Kinase: ULK1 247 The Structure of ULK1 247 The ULK1-mAtg13-FIP200-Atg101 Complex 248 Expression, Transcriptional Regulation, and Posttranscriptional Modification of ULK1 248

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Discussion 255 Acknowledgments 255 References 255

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Abstract

Unc-51-like protein kinase 1 (ULK1), the mammalian homology of Atg1, is not only the initial protein during autophagy but also the exclusive serine/threonine protein kinase so far identified in the core autophagic pathway. Autophagy can be normally divided into five stages: induction, vesicle nucleation, vesicle elongation, docking and fusion, degradation and recycling. Activation of ULK1 by upstream signals, including AMPK and mTOR, can trigger autophagy under different stress conditions. ULK1, FIP200, mAtg13, and Atg101 form a protein complex that can be regulated by posttranslational modifications, such as phosphorylation and acetylation. In addition the common downstream regulator of ULK1 complex includes the phosphoinositide 3-kinase (PI3K) class III-Beclin-1 complex. Interestingly, both the transcriptional regulations of ULK1 complex and posttranscriptional modifications of it varies in different cancers,


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making ULK1 a promising therapeutic target and a diagnostic marker. In addition, considering the dual role of autophagy across various cancers, ULK1 can either promote tumor development or suppress tumor growth based on distinct conditions. Recently, few small-molecule compounds have been discovered that can target ULK1 with antitumor capacities. Therefore the elucidation of the function of ULK1 in cancer should benefit the future discovery of novel antitumor drugs and the combination therapy in cancers.

INTRODUCTION Autophagy, as a highly conserved lysosomal degradation process in eukaryotic cells, can digest long-lived proteins and damaged organelles through vesicular trafficking pathways. Macroautophagy, microautophagy, chaperone-mediated autophagy (CMA) are three identified types of autophagy (Green and Levine, 2014); microautophagy directly engulfs cytoplasm in a lysosome-dependent manner in mammals; CMA refers to selective binding of single proteins and hsc70, which is followed by transportation into the lysosomal lumen. The most known autophagy is macroautophagy (hereafter abbreviated as autophagy), which involves a double-membrane cytoplasm cargo that is termed the autophagosome. By this means, autophagy both serves as a removal system of intracellular components or as a recycling mechanism that benefits of molecular building. In addition, under various stress conditions, such as energy deprivation or DNA damage, it may be strongly enhanced (Bhogal et al., 2012). ATG1 is the first identified autophagy-related gene (ATG) in yeast, and a phosphorylationdependent regulatory mechanism, including Atg1 and seven other interacting proteins, has been described (Chan and Tooze, 2009). The nematode homolog of Atg1, uncoordinated-51 (Unc-51), has corresponding and additional neuronal functions. Five Atg1-closely related kinases are encoded by vertebrate genomes, but only Unc-51-like protein kinase 1 (ULK1) and ULK2 have autophagic functions and an extra neuron-specific vesicular trafficking process (Alers et al., 2012). The cellular events during autophagy are normally divided into five stages, including induction, vesicle nucleation, vesicle elongation, docking and fusion, degradation and recycling (Wen et al., 2013). Molecular regulation in autophagy includes preinitiation ULK1 complex, initiation class III phosphatidylinositol 3-kinase complex, and two ubiquitin-like (Ub-like) protein conjunction systems. Preinitiation complex is formed by ULK1, mAtg13, focal adhesion kinase (FAK) family interacting protein of 200 KDa (FIP200), and Atg101 and can be triggered by stress signals, such as starvation of amino acid or serum, low energy, and glucose deprivation. Notably, Atg13 and FIP200 are essential for the localization from ULK1 to the isolation membrane of autophagosome; in other words, the absence of either of them blocks such process. Homeostatic regulators, such as mammalian TOR complex 1 (mTORC1) and AMP-activated kinase (AMPK), can activate ULK1 through posttranslational modifications (Löffler et al., 2011). MTOR is one of the most critical regulators of ULK1 complex; it directly phosphorylates ULK1 and thus inactivates it. Besides, mTORC1 controls Atg9 trafficking, which is the sole autophagic multiple spanning membrane protein (Chan, 2009). AMPK, as an energy sensor, may induce ULK1 activity by inhibiting mTORC1 and directly phosphorylating ULK1 under the starvation stress. Moreover, GSK3 can trigger ULK1dependent autophagy via TIP60. Then mammalian ULK-mAtg13-FIP200-Atg101 complex (>1 MDa) complex releases the downstream signals and induces the binding of phagophores

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together with the Class III PI3K complex, which consists of Beclin-1, Atg14L, Vps34, and Vps15 (Kang et al., 2011). Then two Ub-like conjugation systems, Atg12-Atg5-Atg16L complex and PE-modified LC3, correlate to actuate membrane expansion and fusion. LC3 family is the mammalian homolog of Atg8, firstly identified in yeast, mammalian genome encodes several Atg8-like molecules, called LC3, GABARAP, and GATE-16, among which LC3 and GABARAP have multiple family members. The Atg12-5-16 complex recruits the LC3 conjugation machinery, then LC3 carboxy-terminal lipid modification leads to autophagosome formation, suggesting these two complex are intimately linked. Furthermore, LC3 family members can recruit LC3-interacting region containing proteins to the membrane of autophagosome. In the last stage of autophagy the target cellular components are degraded in the docking complex of autophagosome and lysosome (Bhogal et al., 2012). This chapter mainly focuses on the ULK1-mAtg13-FIP200-Atg101 protein complex, its function in autophagy initiation and cancer development, as well as the additional cancer therapeutic application of this complex. Since the dual role of autophagy in cancers, ULK1 can promote as well as suppress cancer development. As the only serine/threonine kinase in the core autophagic pathway, the inhibitor of ULK1 can be a future and potential strategy in cancer therapy. In addition the molecular basis and machinery of cancer still need to be elucidated; also distinguishing the role ULK1 plays across distinctive cancers should benefit the future drug discovery.

THE SERINE/THREONINE PROTEIN KINASE: ULK1 The Structure of ULK1 Atg1, first identified in Saccharomyces cerevisiae by genetic screens, has an essential role downstream of the nutrient sensor, TOR. It has a few binding partners, such as Atg13, Atg15, Atg17, Atg20, Atg24, Atg29, and Atg31. Of these proteins, Atg1 and Atg13 have roles for both autophagy and autophagy-related cytoplasm-to-vacuole targeting (Cvt) functions. On the contrary, Atg17, Atg29, and Atg31 function specifically in autophagy, while Atg11, Atg20, and Atg24 only have Cvt pathway functions (Mizushima, 2010). There are five Atg1 orthologs encoded by vertebrate genomes, ULK1/2/3/4 and STK36, and only ULK1 and ULK2 function to regulate autophagy. Human ULK1 holds an overall similarity of 41% to Unc-51, its homolog in Caenorhabditis elegans, and a similarity of 29% to Atg1. Comparing to the other related kinases ULK3, 4, and STK36 in which the similarity is restricted to the N-terminal catalytic domain, the similarity between ULK1 and Atg1 comprises the entire protein, including the N-terminal catalytic domain, the central proline/ serine-rich (PS), and C-terminal domain (CTD) (Wong et al., 2013). N-terminal kinase domain (residue 16–278) and CTD (residue 833–1050) of ULK1 in Homo sapiens are highly conserved. And a PS region, containing sites for posttranslational modifications, locates between the kinase domain and CTD. ULK2 has overall 52% amino acid identities with ULK1; therefore it is suspected to compensate ULK1 functions or contain its own roles in initiating autophagy. An RNAi-based screen identified that ULK1, not ULK2, involves as a critical component in amino acid starvation–induced autophagy (Chan et al., 2007). Beyond that, the knockdown or dominant-negative mutants of ULK1 can lead

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to the block of autophagy, suggesting that ULK1 is an indispensable autophagic protein kinase. Furthermore, CTD, as a highly conserved region, potentially carries out other significant functions. The changes of autophosphorylation and conformation with CTD exposure, as well as maps of the regions that involves directly membrane association and interaction between ULK1 and mAtg13, identified the dominant-negative activity of a 7-residue motif inside CTD in the kinase-dead mutants. That points out that the function of CTD may not limit in binding with mAtg13, but also may interact with other related proteins (Chan et al., 2009). Furthermore the results of a siRNA screening identify that deletion of the PDZ domain-binding Val-Tyr-Ala motif of CTD generates a potent dominant-negative kinase, offering proof for multiple function modules of ULK1.

The ULK1-mAtg13-FIP200-Atg101 Complex Sharing both high identity and similarity of the kinase domain sequence, ULK1 is a counterpart in mammalian autophagy compared to its homolog in other organisms, such as Atg1 or Unc-51, which have been confirmed to exert their function by forming complex except reacting alone. Nevertheless, there are differences of formed complex between Atg1 and ULK1; for instance the complex of Atg1 is formed with Atg13 and Atg17 in yeast, while the mammalian homolog of Atg17 has not been founded yet. The mAtg13 is the mammalian homolog of Atg13, while FIP200 has no counterparts in yeast. In addition, a research verified FIP200 as an indispensable factor for initiating generation of autophagosome with interaction with ULK1 (Fig. 12.1). Thus, conjecture of that FIP200 might be the mammalian functional counterpart of Atg17 and specific binding partner of ULK1 are putting forward. With more notable achievements, it has confirmed now that a quaternion complex is formed by ULK1 with mAtg13, FIP200, and Atg101, interacting with each other to convey downstream signals. MAtg13-binding sites on ULK1 was mapped to C-terminal regions containing residues 829–1051; recently the binding site of ULK1/2-mAtg13 is established by an extremely short peptide motif at the C terminus of ATG13, composed of the last 3 amino acids TLQ480 (Hieke et al., 2015). Under normal conditions, mAtg13 and FIP200 majorly function to regulate the kinase activity of ULK1: either alone can do so when short of the other, to put in another way, to reach the maximal activity of ULK1 needs both, indicating the essential role of this complex during autophagy-induced ULK1 translocation. Besides that, mAtg13 also enacts with FIP200, but whether under ULK1-independent conditions, mAtg13 and FIP200 can function to the initiation of autophagy remains to be researched. Although the precise function of Atg101 have not been understood, it is an essential component of the ULK complex in higher eukaryotes, and it has no homolog or functional equivalent in budding yeast. Recently, mutational studies revealed that a newly identified WF finger of Atg101 recruits downstream factors to the autophagosome formation site (Suzuki et al., 2015).

Expression, Transcriptional Regulation, and Posttranscriptional Modification of ULK1 ULK1 ubiquitously expresses in normal tissues and localizes to autophagosomal membranes, the detection of ULK1 mRNA levels in heart, brain, spleen, lung, liver, and skeletal muscle varies, as well as ULK2, indicating ULK1/2 ubiquitously but diversely expressed in

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FIGURE 12.1 ULK1 in Homo sapiens and homologs in other model organisms. (A) Sequence analysis of ULK1 comparing to other homologs of model organisms. (B) Crystalline structure of ULK1. (C) Comparison of preinitiation complex in model animals. ULK1, Unc-51-like protein kinase 1.

tissues. MicroRNAs (miRNAs) participate in regulation of the ULK1 expression under conditions. For instance, miR-20a and miR-106b, two members of the miR-17 family, suppress ULK1 expression to regulate leucine deprivation–induced autophagy in C2C12 myoblasts. Deprivation of leucine can reduce the expression of miR-20a and miR-106b by suppressing

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transcription factor c-Myc; in addition, treatments of miR-20a or miR-106b mimic reduce levels of endogenous ULK1 (Wu et al., 2012). Furthermore the miR-290–295 cluster strongly upregulates ULK1 in melanoma cells under chronic deprivation of nutrient conditions, and overexpression of miR-290–295 cluster renders resistance to glucose starvation (Chen et al., 2012). As revealed in yeast, three major groups, including Atg1 complex, enable the localization of Atg proteins to the preautophagosomal structure (PAS) during the early stage of autophagy. There is no such evidence so far indicating the existence of PAS in mammals, but ULK1-mAtg13-FIP200-Atg101 complex may have the potential to exert the same function. Serine/threonine phosphorylation mainly mediates the nutrient- and stress-dependent cellular responses, the alteration of ULK1 complex phosphorylation status is regulated by relevant upstream signaling pathways during autophagosome formation. ULK1 complex is majorly mediated by stress sensors, such as mTORC1 and AMPK. mTORC1 is a negative regulator of autophagy and formed by raptor (KOG1 ortholog), GbL/mLst8, PRAS40, and DEPTOR (Jung et al., 2010). Under normal conditions, AMPK is inactive, and mTORC1 remains in association with the ULK1 complex by direct interacting between raptor and ULK1. AMPK is activated when ATP/AMP ratio decreases, then it inhibits mTORC1 directly or by the TSC1/2-Rheb pathway. The interaction between AMPK and mTORC1 leads to the phosphorylation of mTORC1, thus results in disassembling of mTORC1 and ULK1 and activating ULK1 complex in conducting autophagosome formation (Fu et al., 2012). AMPK can directly interact with the ULK1 complex in mTORC1deficient tests, providing evidence for compensation regulation between ULK1 and AMPK. MTORC1-dependent autophagy mainly responses to nutrient starvation, induced by starvation of amino acid and serum. Growth factor signaling regulates mTORC1 mainly by the insulin/insulin-like growth factor (IGF-1)-PI3K-Akt pathway. The insulin/IGF-1 pathway contains both positive regulators of mTORC1, such as PDK1 and Rheb, and the negative regulators, such as PTEN and TSC2. Furthermore, PRAS40 served as a substrate of Akt, thus mediates insulin signaling pathway. Besides those previously mentioned modification of the ULK1 complex during autophagic process, the ULK1 complex also has intricate phosphorylations and other posttranscriptional modifications, such as ubiquitination and acetylation.

THE EXPRESSION OF ULK1 IN DIFFERENT CANCERS In comparison to normal cells, the expression of ULK1 alters in some types of cancer cells, including breast cancer, hepatocellular carcinoma (HCC), and colorectal cancer (CRC), which suggests that ULK1 can be a prognostic marker of cancers. In operable breast cancer, low expression of ULK1 is associated with cancer progression, thus acting as an adverse prognostic marker of survival for patients. Researchers also revealed that both the levels of ULK1 mRNA and protein decrease in breast cancer tissues, and tumor size, many index, including lymph node status and pathological stage are negatively correlated with ULK1 expression. Not only in breast cancer but also in HCC, the expression of ULK1 varies between adjacent peritumoral tissues and HCC tissues, and low expression of ULK1 is in prominent association with tumor size (Xu et al., 2013). Moreover, even though the

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expression of ULK1 in CRC distribute from high to low levels, it seems that high expression levels of ULK1 are one of the risk factors for overall and disease-free survival, indicating that ULK1 may be a useful independent biomarker for predicting a poor prognosis in patients with CRC (Zou et al., 2015). Furthermore, in basal cell carcinoma (BCC), the overexpression of GLI1 may significantly increase the expression level of ULK1 and another neuronal differentiation marker, ARC (Gore et al., 2009). However the expression level of ULK1 in other types of cancers has not public data, with more research of such area, the potential of ULK1 being a biomarker in cancers may be discovered, as well as potential uses in cancer diagnosis.

ULK1 PROMOTE TUMOR GROWTH Autophagy has been well known for its dual role functions in cellular process, which is cytoprotective autophagy and cytotoxic autophagy (also called autophagic cell death). During the cancer proliferation and growth, traits of cytoprotective autophagy benefit cancer cell in various settings, including genome instability, survival under nutrient starvation, hypoxia, excessive ROS, and so on. In addition, autophagy may contribute to chemoresistance when patients are under treatment. Therefore the cytoprotective autophagy may be a valuable target to suppress cancer growth, since ULK1 complex is an autophagic initiator, elucidation of its role in cancer development has attracted much attention. ULK1 can promote the cancer cell viability by enabling cancer cell survival under hypoxia, a significant feature of tumor cells in vivo contributed to the mismatch between the high proliferative rates and the shortage of the blood supply to provide nutrients. In severe hypoxic circumstances the expression levels of ULK1 changes to regulate different signals. In primary human head and neck squamous cell carcinoma (HNSCC) the enrichment of ULK1 occurs in hypoxic tumor regions, which suggests that ULK1 high enrichment might be a trait of a high hypoxic fraction. In addition, active transcription factor 4 (ATF4) can upregulate transcriptional mRNA and protein expressions in hypoxia, including ULK1, then contribute to cancer cell survival. Furthermore, severe hypoxia may leads to endoplasmic reticulum (ER) stress. To protect cells from ER stress, ULK1 also participates in the integrated stress response, and ablation of ULK1 results in caspase-3/7-independent cell death (Pike et al., 2013). Small-molecule compounds or natural products can influence cytoprotective autophagy by targeting other parts of ULK1 complex and related network in autophagic core machineries. Inhibition of phospholipase D (PLD) can induce autophagic flux via ULK1, Atg5, and Atg7, thus acting as an autophagic regulator. PLD suppresses autophagy by phosphorylating ULK1, which is majorly mediated by mTOR and AMPK (Nazio et al., 2013), leading to the inhibition of the cancer cells regression. Platycodin D (PD) triggers apoptosis and protective autophagy through activation of extracellular signal-regulated kinase in HCC HepG2 cells, as evidenced by the increased phosphorylation of Akt, mTOR, and ULK1 (Ser757). Nevertheless the PD-induced proliferative inhibition and apoptosis can remarkably enhance with autophagy inhibitor chloroquine (CQ) or bafilomycin A1 (BAF), suggesting the combined treatment with PD and CQ or BAF may provide a promising regimen for HCC therapy (Li et al., 2015) (Fig. 12.2).

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FIGURE 12.2 The regulation network of ULK1 in autophagy. AMPK activates ULK1 under low energy or glucose deprivation, meanwhile mTORC1 is mainly inhibited under amino acid or serum starvation. And GSK3 is activated by the removal of growth factors; then GSK3 phosphorylates TIP60 at Ser86, which increases acetylation and kinase activity of ULK1. The Atg proteins required for mammalian autophagy are now classified into six functional groups: the ULK1 complex; Atg9; the class III phosphatidylinositol (PI)3-kinase complex (Beclin-1-Atg14L-Vps15Vps34); the PI(3)P-binding Atg2-Atg18 complex; the Atg12 conjugation system (Atg12-Atg5-Atg16); and the LC3 conjugation system (LC3-PE). ULK1, Unc-51-like protein kinase 1; AMPK, AMP-activated kinase; GSK3, glycogen synthase kinase-3.

ULK1 SUPPRESS TUMOR GROWTH Besides cytoprotective autophagy, cytotoxic autophagy or autophagic cell death also largely distribute in cancers. Positive regulators of autophagy, such as Beclin-1, are tumor suppressors (Qiu et al., 2014), and there are a few compounds processing the anticancer abilities by inducing autophagic cell death. For example, Rapamycin targets mTORC1, and Tamoxifen, a well-known drug of breast cancer, increases the expression of Beclin-1. Baicalein induces autophagic cell death rather than apoptosis to suppress cancer development by activation of AMPK/ULK1 and downregulation of mTORC1 components in cancers. Evidence of baicalein suggests that the induced cell death can be reversed by inhibiting key autophagic molecules, such as Beclin-1, Vps34, Atg5, and Atg7, but not pan-caspase inhibitor (Aryal et al., 2014).

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Long noncoding RNAs (lncRNAs) PTENP1 is a pseudogene of the tumor suppressor gene PTEN, the treatment of lncRNA PTENP1 in HCC can significantly restore the expression of PTEN, and decoye oncomirs miR-17, miR-19b, and miR-20a. Those miRNAs can increase the expression of autophagic genes, including ULK1, thus trigger autophagic cell death and suppress HCC (Chen et al., 2015). Treatment of Tetrandrine decreases SAS human oral cancer cells viability via induction of autophagic cell death, which is proved by augmentation of p-ULK1 and p-mTOR levels. Tithonia diversifolia methanolic extract significantly aggrandize the expression of ULK1 and LC3II, thus leading to the autophagic cell death in human glioblastoma U373. Raloxifene induces autophagic cell death in breast cancer cells via the activation of AMPKULK1 pathway and can be blocked by autophagy inhibitor 3-methyladenine or siRNA of Beclin-1 (Kim et al., 2015). Temozolomide induces autophagy via ATM-AMPK-ULK1 pathways in glioma (Zou et al., 2014). Notwithstanding, it is noteworthy that a log-rank test revealed that ULK1 might be related to the metastasis, as metastasis contributing to more than 90% of cancer deaths. Cancer patients with lower level expression of ULK1 relate to a significant shorter time of both distant metastasis-free and cancer-related (Egan et al., 2011). However, considering there are numerous open questions about the two-side role of autophagy in cancer, ULK1 are still a complicated but potent target toward cancer therapies (Fig. 12.3).

THERAPEUTIC STRATEGY FOR TARGETING ULK1 IN CANCERS Autophagy attributes to both cancer growth and suppression, the complicated relationship between autophagy and cancer obscures the development of anticancer therapies. Extensive studies over the past decade have implicated the role of autophagy in maintenance of cancer cell survival or fatal destinies, which also furnished the justifying potency in targeting autophagy in cancer therapy. As mentioned earlier, ULK1 is the only serine/ threonine kinase essential during the autophagic machinery. Recently, several ULK1-specific small-molecule compounds, as inhibitors or activators, have broadened our understanding of ULK1 functions and autophagic mechanisms (Pasquier, 2015). Currently a novel highthroughput screening (HTS) compatible method has been developed to identify the kinase activity of ULK1 inhibitors by monitoring the purified ULK1 and phosphorylation level of mAtg13. Based on AlphaScreen technology, this biochemical assay has been optimized and validated via screen of Sigma LOPAC library, confirming that such a method can be robust and reproducible in HTS of novel inhibitors of ULK1 (Rosenberg et al., 2015). Recently, disclosure of the ULK1 structure in complex with compound 6, a potent inhibitor of ULK1, may accelerate the exploitation of ULK1 inhibitors. The research team have screened 764 molecules against ULK1 and confirmed the best hit, compound 6, with a high affinity (IC50 = 8 nM). However, shortcomings of compound 6 are depicted as well, including that the nonspecificity of compound 6 toward ULK1 and the unknown effect of compound 6 during autophagy (Lazarus et al., 2015). Followed researches of this team also identified another potent ULK1 inhibitor, compound 1, with IC50 equals 5.3 nM (Lazarus and Shokat, 2015). MRT67307, a TANK-binding kinase 1 (TBK1) inhibitor, has revealed potent activities toward both ULK1 (IC50 = 45 nM) and ULK2 (IC50 = 38 nM) by the same

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FIGURE 12.3 The dual role of ULK1 in cancers. ULK1 has a dual role in autophagic regulation of cancer cell fates. ULK1 can promote cell survival under hypoxia stress by reducing ER stress, meanwhile hypoxia-related transcriptional changes can increase the expression of ULK1. The anticancer treatment may suppress ULK1 either sole or in combination use. On the other hand, ULK1 suppresses tumor growth by extracellular signals–mediated autophagic cell death. ULK1, Unc-51-like protein kinase 1; ER, endoplasmic reticulum.

biochemical assay as the researcher-discovered compound 6 did. In addition, another TBK1 inhibitor MRT68921, an analog of MRT67307, processes a decouple affinity increased in comparison with MRT67307 on ULK1, with IC50 = 2.9. Nevertheless the nonspecificity toward ULK1 also exists in MRT67307 and MRT68921. In addition MRT68921 inhibits autophagy in ULK1/2 double-knockout MEF cells, even under the reconstitution with wildtype ULK1; while it cannot inhibit autophagy when reconstituted with ULK1 mutant, which has mutation retaining kinase activity in the gatekeeper residue M92T, suggesting that MRT68921 inhibit autophagy in an ULK1-dependent manner (Petherick et al., 2015). An FAK inhibitor, SBI-0206965, is also identified as inhibitors of ULK1 (IC50 = 108 nM) and ULK2 (IC50 = 711 nM) inhibitor. Being different from the previously mentioned biochemical assay, researchers identified the phosphorylation level of Vps34 in Ser249 that is catalyzed by ULK1 to measure the activity of ULK1 under the treatment of compounds in HEK293T cells with overexpression of Vps34. This compound inhibits AZD8055, an mTOR inhibitor, induced autophagy, suggesting a synergized capacity with mTOR inhibitors in

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anticancer combinational uses. But with the dosage of in vitro experiment, SBI-0206965 showed the inhibition toward multiple kinases (Egan et al., 2015). Until now, several compounds or other signals that have been identified can activate AMPK/ULK1 to induce autophagy, including Baicalein (Aryal et al., 2014), nitric oxide (Xing et al., 2014); no specific activator of ULK1 has been depicted. In addition, those novel identified ULK1 inhibitors with high potency in biochemical assays still lack specificity toward ULK1, accounting for the early stage of ULK1-specific targeting drug discovery. Both the optimization of those chemical probes and specific design for ULK1 structure should benefit the potential ULK1-related drug discovery, as well as the mechanism studies (Egan et al., 2015).

DISCUSSION Even with numerous open questions needed to be addressed, there are significant progresses being made recently. The distinctive expression of ULK1 in cancer cells compared to normal tissues suggests that it can be a diagnosis biomarker of different cancers, such as breast cancer and HNSCC. And the essential role of ULK1 in autophagy initiation has made it a promising therapy target; currently the ULK1 structure has revealed that it can largely accelerate the drug discovery process. A few small-molecule compounds with anticancer capacities have been identified that may directly target ULK1 and regulate autophagy, while novel biochemical assays are developed and applied in the recent drug discovery. Even though those novel compounds are short of the specificity of ULK1 in cancer cells, they may provide enlightening opinions for future researches.

Acknowledgments This work was supported by grants from National Natural Science Foundation of China (81473091).

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13 X-Box-Binding Protein 1 Splicing Induces an Autophagic Response in Endothelial Cells: Molecular Mechanisms in ECs and Atherosclerosis Sophia Kelaini, Rachel Caines, Lingfang Zeng and Andriana Margariti O U T L I N E Introduction 260 Atherosclerosis 260 Autophagy 261 Autophagy and Atherosclerosis 262 X-Box Binding Protein 1 262 XBP1 and ER Stress Response 263 Discussion 264 XBP1 Role in ECs, Atherosclerosis, and Autophagy 264

BECLIN-1 264 XBP1 mRNA Splicing and BECLIN-1 264 XBP1 Mechanism Is Cell-Type Dependent 266 Summary 266 References 266

Abstract

Atherosclerosis is the leading cause of death in the developed world and involves the production of an atherosclerotic plaque in the artery wall, limiting blood flow and resulting in conditions such as peripheral artery disease, coronary heart disease, myocardial infarction, and stroke. Autophagy is a method of


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self-digestion, primarily a survival pathway for the cell, to remove and/or recycle old and damaged proteins in the cytoplasm. There is increasing evidence that autophagy takes place in severe atherosclerotic plaques implicating macrophages and vascular smooth muscle cells. In addition, oxidized low-density lipoprotein (Ox-LDL) can also trigger autophagy in endothelial cells (ECs) through LC3β/BECLIN-1, leading to the lysosome-mediated degradation of Ox-LDL. However the role of autophagy in atherosclerosis still remains shrouded in mystery, as it is still debated whether autophagy is a damaging or a protective mechanism or a balance of both is needed for normal cellular function. X-Box binding protein 1 (XBP1) mRNA splicing is involved in the regulation of autophagy in ECs through BECLIN-1 transcriptional activation. It has recently been shown that sustained activation of XBP1 results in EC apoptosis and development of atherosclerosis. More evidence has shown the importance of XBP1 in eliciting an autophagic response in ECs. Therefore, it seems that the threshold of the autophagic responses could be determined through the tight regulation of the expression and duration of splicing activation of molecules, such as XBP1s, in a cell-specific manner.

INTRODUCTION Atherosclerosis Atherosclerosis is the leading cause of death in the developed world and involves the production of an atherosclerotic plaque in the artery wall, limiting blood flow and resulting in conditions such as peripheral arterial disease, coronary heart disease, myocardial infarction, and stroke (Ross, 1999). It is thought that atherosclerosis is a long-term inflammatory disease of the vascular endothelium to which individuals can be predisposed due to multiple risk factors such as sex, genetic make up, dyslipidemia, hypertension, diabetes, and obesity (Libby et al., 2002). The simple endothelial monolayer plays a large role in vascular homeostasis regulating the tone of the vasculature, cellular adhesion to the blood vessel walls, inflammation of the vessel walls, and thromboresistance; therefore the endothelium disturbance or dysfunction leads to serious pathological changes usually mediated through environmental changes in the levels of the potent vasodilator nitric oxide (NO) (Park and Park, 2015). NO, produced through endothelial nitric oxide synthase (eNOS), provides the endothelium with the majority of its homeostatic features by inhibiting aggregation of platelets, inflammation, oxidative stress, vascular smooth muscle cell (VSMC) migration and proliferation, and leukocyte adhesion (Park and Park, 2015). Many of the aforementioned risk factors place a large amount of oxidative stress on the endothelium leading to the production of reactive oxygen species (ROS) which in conjunction with superoxide dismutase produce hydrogen peroxide. The hydrogen peroxide is capable of reacting with cysteine groups within proteins to alter their structure and therefore their function. Some of the consequences of these changes can be the phosphorylation of transcription factors, nuclear chromatin remodeling, and protease activation. eNOS is also affected here, becoming uncoupled and producing yet more superoxide ions. This can be a part of normal host defense, but during chronic production of ROS in pathologies such as diabetes, the scavenging mechanisms become overwhelmed and the endothelium begins to lose function and atherosclerotic disease is initiated (Deanfield et al., 2007; Park and Park, 2015). The inflamed endothelial wall begins to upregulate a number of inflammatory markers leading to adhesion of monocytes that migrate into the intima and become fat-laden macrophages or foam cells. The activated macrophages secrete matrix metalloproteinases, which

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degrade collagen in the surrounding plaque tissue, weakening the fibrous cap (Libby et al., 2002). The migration and then death of VSMCs are also induced by macrophages within the lesion by Fas/Fas-L interactions, decreasing any stability the VSMCs may provide to the plaque and resulting in the production of a more advanced, weakened lesion prone to rupture (Martinet and De Meyer, 2009). It is therefore reasonable to say that VSMCs would stabilize the plaque, whereas macrophages promote destabilization of the plaque. VSMCs which have begun to disintegrate in the atherosclerotic plaque have been studied by transmission electron microscopy and have been shown to demonstrate a number of autophagic-like features such as numerous vacuoles and myelin figures, which are evidence of the degradation of cellular components (De Meyer and Martinet, 2009; Martinet and De Meyer, 2009).

Autophagy Autophagy is a method of self-digestion, primarily a survival pathway for the cell to remove and/or recycle old and damaged proteins in the cytoplasm. This allows amino acids and fatty acids to be freed up for the production of new proteins or ATP as the cell demands. Autophagy involves the formation of a double-membrane-bound vacuole, otherwise known as an autophagosome. This will then incorporate with a lysosome to produce an autophagolysosome. The inner membrane of this double-membraned vacuole along with its cytoplasmic contents are degraded by a number of lysosomal hydrolases. Although autophagy is carried out at a basal level in the cell, it is a highly contested topic in terms of disease to understand if the upregulation of autophagy is purely the cell that is working harder to survive, or is it actually contributing further to cell death and in terms of atherosclerosis, through macrophages, promoting plaque destabilization and rupture leading to a thrombotic event. Initial autophagy in VSMCs is hypothesized to contribute to plaque stability through the promotion of VSMC survival by protecting against oxidative stress by degradation of damaged material such as polarized mitochondria before they begin to release cytochrome c, which would then induce apoptosis in the cell (Kiffin et al., 2006). Conversely, during times of excessive oxidative stress in conditions such as diabetes, autophagy becomes excessively stimulated leading to VSMC death. The saturation of scavenging mechanisms and thus excess of ROS lead to damaged proteins and cellular components that cannot be cleared. This is due to ROS-induced damage of the lysosomal membrane, preventing fusion with the autophagosome and damaged components cannot be cleared. In the chance that the lysosomal membrane becomes so damaged that it ruptures, healthy cellular components become exposed to the strong lysosomal hydrolases further increasing the damage to any remaining healthy portions of the cell (De Meyer and Martinet, 2009). As defense mechanisms continue to be overwhelmed, atherosclerotic autophagy leads to the formation of ceroid, an insoluble protein found in association with oxidized lipids, something characteristic of all atherosclerotic plaques. Intra or extracellular colocalization of iron and ceroid deposits in foam cells or VSMCs. These deposits cannot be cleared by lysosomal hydrolases and tend to harbor the enzymes in ceroid-loaded lysosomes leading to the inactivation of autophagy, accumulation of damaged mitochondria, and promotion of apoptosis (De Meyer and Martinet, 2009).

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Autophagy and Atherosclerosis There is increasing evidence that autophagy takes place in severe atherosclerotic plaques (Schrijvers et al., 2011) implicating macrophages (Liao et al., 2012) and VSMCs (Hu et al., 2012). In addition, oxidized low-density lipoprotein (Ox-LDL) can also trigger autophagy (Han et al., 2011) in endothelial cells (ECs) through LC3β/BECLIN-1, leading to the lysosome-mediated degradation of Ox-LDL (Zhang et al., 2010). Furthermore, induction of autophagy promotes angiogenesis through activation of vascular endothelial growth factor (Du et al., 2012). However the role of autophagy in atherosclerosis still remains shrouded in mystery, as it is still debated whether autophagy is a damaging or a protective mechanism (Levine and Yuan, 2005) or a balance of both is needed for normal cellular function. For example, it was shown that activation of caspase, a molecule involved in the apoptotic machinery, regulates the cellular export of autophagic vacuoles, showcasing that apoptosis and autophagy are very closely associated (Sirois et al., 2012). There are a number of features of the atherosclerotic environment known to stimulate autophagy such as oxidized lipids (Kiffin et al., 2006), endoplasmic reticulum (ER) stress (Marciniak and Ron, 2006), inflammation (Deretic, 2006), hypoxia, and metabolic stress (Karantza-Wadsworth et al., 2007) mostly through further oxidative stress. ER stress leads to the stimulation of the unfolded protein response (UPR) particularly within lesion-associated macrophages (Martinet and De Meyer, 2009; Zhou et al., 2005).

X-Box Binding Protein 1 X-box binding protein 1 (XBP1) is a protein encoded by the XBP1 gene in humans (Liou et al., 1990). Its gene is localized on chromosome 22 while a similar pseudogene has been found to be located on chromosome 5 (Liou et al., 1991). This protein is a transcription factor regulating the expression of genes crucial to the appropriate functioning of the immune system as well as in stress response of a cell (Yoshida et al., 2006a). XBP1 mRNA splicing has been shown to be implicated in affecting plasma cell differentiation (Reimold et al., 2001), foetal survival, and liver development (Clauss et al., 1993; Reimold et al., 2000). The XBP1 transcription factor contains a basic leucine zipper domain (bZIP domain), which is found in many DNA-binding proteins in eukaryotes. Part of this domain contains a section that can mediate sequence-specific DNA-binding properties. It also contains a “leucine zipper” that is necessary for the dimerization of two DNA-binding regions (Clauss et al., 1996; Liou et al., 1990). The DNA-binding region includes various common amino acids such as arginine and lysine. XBP1 was initially identified by its ability to bind to the X-box, a conserved promoter transcriptional element in the human leukocyte antigen DR alpha (Liou et al., 1990). Expression of the XBP1 protein is necessary for the transcription of a number of Class II Major histocompatibility (MHC Class II) genes (Ono et al., 1991). In addition, XBP1 heterodimerizes with other transcription factors, containing a bZIP domain, such as c-fos (Ono et al., 1991). XBP1 expression is regulated by the interleukin 4 cytokine as well as the antibody Ig mu chain C region (Iwakoshi et al., 2003). Subsequently, XBP1 controls the expression of interleukin 6, which promotes growth of plasma cells as well as that of immunoglobulins in B lymphocytes (Iwakoshi et al., 2003). XBP1 is also important for the differentiation of

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antibody-secreting plasma cells (Iwakoshi et al., 2003). The differentiation process necessitates not only the XBP1 being expressed but also the expression of the spliced isoform of XBP1 (Hu et al., 2009). Proper expression of XBP1 is important for the normal function of two crucial plasma cell differentiation genes, IRF4 and Blimp-1. In fact, it has been shown that XBP1-negative plasma cells fail to colonize their niches in the bone marrow or to maintain antibody secretion (Hu et al., 2009). XBP1 protein has also been recognized as a cell transcription factor, which can bind to an enhancer in the T-cell leukemia virus type 1 promoter region (Ku et al., 2008). The XBP1 generation during plasma cell differentiation also seems to be the starting prompt for the reactivation of latent Kaposi’s sarcoma-associated herpesvirus and Epstein Barr virus. XBP1 may boost viral protein expression by acting as the DNA-binding partner of a virus transactivator (Kati et al., 2013). XBP1, a member of the basic region/leucine zipper transcription factor family, plays key roles in plasma cell differentiation and liver growth and has found to be a signal transducer significantly upregulated in the ER stress response (Marciniak and Ron, 2006; Yoshida et al., 2001). During times of stress, XBP1 mRNA can become spliced through the actions of inositol-requiring enzyme-1α causing an open reading frameshift and forming a 56-kDa spliced protein isoform (XBP1s) in comparison to the 29-kDa unspliced isoform (XBP1u) (Lee et al., 2002; Yoshida et al., 2001). It has been shown that sustained activation of splicing at branch points of blood vessels leads to EC apoptosis and atherosclerosis (Zeng et al., 2009). A study by Zeng et al. (2009) showed that both splicing isoforms were highly expressed in areas susceptible to atherosclerosis, such as branch points in the arteries where ECs are under much more stress. Disturbed flow also increased XBP1u and XBP1s expression in comparison to usual laminar flow found in healthy blood vessels. When human umbilical vein ECs were observed, higher XBP1s was found in proliferating cells in comparison to quiescent cells which is mirrored in atherosclerosis with those ECs at branch points undergoing proliferation and apoptosis while those in areas of laminar flow do not tend to divide. A number of caspases were shown to be activated by XBP1s in ECs, which may promote EC dysfunction and overexpression of XBP1s leads to EC apoptosis in vivo and loss of ECs from blood vessel walls ex vivo. The experiment, which confirmed that XBP1 was a key inducer of atherosclerotic features, was the overexpression of XBP1s in straight, nonbranched sections of the artery, which resulted in neointima formation, VSMC proliferation, and monocyte infiltration. At this point it was still unknown how XBP1s mediated this effect.

XBP1 and ER Stress Response XBP1 is part of an ER stress response, the so-called UPR (Iwakoshi et al., 2003). It has been found that conditions that surpass the coping ability of the ER incites ER stress and activates the UPR. In particular the accumulation of unfolded proteins in the ER causes the mRNA product of XBP1 to be transformed to an active form using an alternative splicing mechanism that is mediated by the endonuclease inositol-requiring enzyme 1 (IRE1) (Margariti et al., 2013). As a result, GRP78, a central regulator of the ER, is released from IRE1 to support protein folding (Kaufman, 1999). More specifically, IRE1 catalyzes the excision of an unconventional intron with 26 nucleotides in length from the XBP1 mRNA. Removing this intron results in a frame-shift in the XBP1 coding sequence, which in turn

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leads to the translation of the active XBP1 isoform (Iwakoshi et al., 2003). The isoform encoded by the unspliced (U) mRNA, XBP1(U), is constitutively expressed and thought to function as a negative feedback regulator of spliced (S) XBP1(S), which shuts off transcription of target genes during the recovery phase of ER stress (Yoshida et al., 2006b).

DISCUSSION XBP1 Role in ECs, Atherosclerosis, and Autophagy It has been shown that continued activation of XBP1 mRNA splicing results in EC apoptosis and development of atherosclerosis (Zeng et al., 2009). However the mechanisms that are implicated in the control of autophagy are mostly unknown. As mentioned earlier the XBP1 transcription factor has an unspliced form, with a molecular mass of 29 kDa, as well as a spliced form. The unspliced form acts as a dominant negative of the spliced XBP1 (Sriburi et al., 2004; Zeng et al., 2009). In response to ER stress, XBP1 mRNA undergoes unconventional splicing resulting in the creation of its 56-kDa spliced form. This spliced isoform retains an intact transcriptional activity (Lee et al., 2002; Yoshida et al., 2001). In a recent study it was shown that XBP1 mRNA splicing is involved in the regulation of autophagy in ECs through BECLIN-1 transcriptional activation. Zeng et al. has recently shown that sustained activation of XBP1 results in EC apoptosis and development of atherosclerosis (Zeng et al., 2009). In later experiments by the same group, more evidence was generated regarding the importance of XBP1 eliciting an autophagy response in ECs (Margariti et al., 2013) (Fig. 13.1).

BECLIN-1 BECLIN-1 is one of the proteins critical to autophagy and is the mammalian ortholog of the yeast autophagy protein Apg6/Vps30 (Kametaka et al., 1998). BECLIN-1 can balance errors in yeast autophagy and can also activate autophagy when overexpressed in mammalian cells (Liang et al., 1999). BECLIN-1 is located in cytoplasmic structures including mitochondria, although overexpression of BECLIN-1 reveals some nuclear staining, too (Liang et al., 2001). Mice lacking both alleles of Beclin-1 die early in embryogenesis, whereas mice lacking one Beclin-1 allele have a high occurrence of spontaneous tumors. Stem cells originating from the null mice exhibited a distorted autophagic response, although responses to apoptosis were normal (Yue et al., 2003).

XBP1 mRNA Splicing and BECLIN-1 The above findings provide insights into the cell death machinery of ECs, which is a key event in atherosclerotic diseases. They also reveal the fact that XBP1 mRNA splicing is implicated in the induction of autophagy in ECs through transcriptional regulation of BECLIN-1. Autophagy has also been activated in response to inhibitors of angiogenesis (Nguyen et al., 2007).

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FIGURE 13.1 A schematic of illustration of XBP1 splicing in autophagic response. Upon endostatin or other stimuli treatment the activated IRE1α causes an open reading frame shift in the XBP1 mRNA, giving rise to a 371-amino acid, 54-kDa protein with an activation domain, the XBP1s isoform. The XBP1s translocates into the nucleus and binds as homodimers or heterodimers to the BECLIN-1 gene promoter region at −537 ~ −755 nt upstream of the transcription initiation site. Activation of BECLIN-1 transcription induces autophagic response, leading to cell survival or apoptosis. IRE1α, inositol-requiring enzyme-1α, XBP1, X-Box binding protein 1; XBP1s, 56-kDa spliced protein isoform.

Endostatin is a well-characterized inhibitor of angiogenesis that causes apoptosis (Nguyen et al., 2009) and has been found to induce autophagy in ECs (Chau et al., 2003) and enhance BECLIN-1 expression through β-catenin and Wnt-mediated signaling pathways (Gao et al., 2010). In accordance with these findings, endostatin resulted in activation of autophagic gene expression through XBP1 mRNA splicing in an IRE1α-dependent manner. Targeting of XBP1 or IRE1a by shRNA in ECs eliminated endostatin-induced autophagic gene expression and autophagosome formation (Margariti et al., 2013). BECLIN-1 is an essential autophagic protein, which has a crucial role in the initial stages of autophagy (Maiuri et al., 2007). Previous studies have shown that BECLIN-1 levels and autophagic vesicle formation were regulated by Bcl-2 and Bcl-xL (Nguyen et al., 2009), which are important players in the decision of a cell to progress to an apoptotic or necrotic death (Pattingre et al., 2005).

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To understand the mechanism that implicates the regulation of autophagy by XBP1 splicing in ECs, newer experiments revealed that XBP1 splicing activation prompts BECLIN-1 transcriptional initiation through its direct binding to the BECLIN-1 promoter (nt −537 to −755). A variety of potential transcription factor–binding sites in this promoter region have been identified, including CREBP. This could mean that XBP1s may function as either a homodimer or a heterodimer in conjunction with another transcription factor, namely CREBP. Later experiments shed even more light regarding transcriptional activation mechanism of BECLIN-1 through XBP1, by demonstrating that XBP1s did not cause transcriptional activation of a truncated construct of the pGL3-Luc-BECLIN-1 promoter that lacked the −537 to −755 region. In addition XBP1 has been shown to be involved in the regulation of histone H4 acetylation (Tao et al., 2011), while, at the same time, XBP1s is also an acetylation and deacetylation target, mediated by p300 and SIRT1 (sirtuin 1), respectively (Wang et al., 2011). Furthermore, it has also been shown that IRE1/XBP1 regulates the acetylation status of the ER by controlling the acetyl-CoA influx through a membrane transporter called AT-1, resulting in autophagy regulation in a cell type–dependent manner (Pehar et al., 2012). This could mean that XBP1s controls the transcriptional activation of BECLIN-1 by the enrolment of other acetylation-inducing cofactors as well as cofactors that promote protein stability and/or inhibit deacetylation.

XBP1 Mechanism Is Cell-Type Dependent It has been reported that targeting XBP1 protects against Huntington’s disease through the regulation of FoxO1 and autophagy (Vidal et al., 2012). In addition, XBP1 deficiency increased the severity of spinal cord injury in a mouse model (Valenzuela et al., 2012) but did not change prion-based pathogenesis (Hetz et al., 2008). These results point toward the fact that XBP1-regulated autophagy pathways contributes only to certain diseases with distinct outputs (Vidal et al., 2012). In another example, activation of XBP1 splicing in VSMCs does not induce autophagic response (Margariti et al., 2013).

SUMMARY Thus, it seems that the threshold of the autophagic responses could be determined through the tight regulation of the expression and duration of splicing activation of molecules, such as XBP1s, in a cell-specific manner. Further studies will be necessary to elucidate whether XBP1 mRNA splicing could be used as a significant pharmacological target that could regulate the autophagic machinery.

References Chau, Y.P., Lin, S.Y., Chen, J.H., et al., 2003. Endostatin induces autophagic cell death in EAhy926 human endothelial cells. Histol. Histopathol. 18, 715–726. Clauss, I.M., Gravallese, E.M., Darling, J.M., et al., 1993. In situ hybridization studies suggest a role for the basic region-leucine zipper protein hXBP-1 in exocrine gland and skeletal development during mouse embryogenesis. Dev. Dyn. 197, 146–156.

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14 Small Molecule–Mediated Simultaneous Induction of Apoptosis and Autophagy Sudhakar Jinka and Rajkumar Banerjee O U T L I N E Targeted Chemotherapy-Breast Cancer-mTOR Pathway Cell Death 280 Small Molecular–Weight Cationic Lipids as Anticancer Agents 280 ESC8, A C-8 Cationic Lipid Containing Estradiol as an Anticancer Agent 281

Introduction 270 Apoptosis 270 Extrinsic Pathway of Apoptosis 272 Intrinsic (Mitochondrial) Pathway of Apoptosis 272

ESC8 Is a Potent Anticancer Agent Against ER-Positive and ER-Negative Cancer Cells ESC8 Mediates Intrinsic Apoptotic Pathway in Breast Cancer Cell Lines Induction of Autophagic Cell Death by ESC8 ESC8-PI3K-AKT-mTOR Pathway ESC8 Treatment Leads to Apoptosis and Tumor Regression in Mouse Tumor Model

Autophagy 273 Fundamental Mechanism of Autophagosome Construction 273 Cross Talk Between Apoptosis and Autophagy 274 Intrinsic Apoptosis–Autophagy 275 Extrinsic Apoptosis–Autophagy 275 Breast Cancer

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PI3K-AKT-mTOR Signaling Pathway PI3K-AKT-mTOR Signaling Cell Death PI3K-AKT-mTOR Pathway Cell Proliferation/Cell Cycle P53-mTOR Pathway Cell Death and Cell Survival

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Cell proliferation, differentiation, and death are the three vital processes for maintenance of cell homeostasis. Apoptosis and autophagy are the two key programmed cell death pathways that act in a cell, without affecting the neighboring cells and play roles not only in development and morphogenesis but also in various diseases such as diabetes, cardiovascular diseases, infectious diseases, and cancer. Breast cancer is the leading cancer type in female populations that needs to be prevented or treated. Nowadays several treatments are available for treating breast cancer. Among them targeted chemotherapy plays a crucial role. The drugs available for breast cancer may act in two different ways either by decreasing cell proliferative pathways or by increasing cell death pathways in cancer cells. These drugs mainly target three important hormone receptors (estrogen, progesterone, Her2) whose levels are high in breast cancer especially at primary stage. ESC8 is one such drug that is designed to target estrogen receptor, but the results were astonishing as it showed its action not only on estrogen receptor (ER)-positive cells but also on ER-negative cell lines. Though the exact mechanism of action of ESC8 is not well understood, the results show that ESC8 acts through downregulation of mTOR protein levels via PI3k-AKT-mTOR signaling pathway, which is activated in most of the cancers and is probably one of the targets of ESC8. Simultaneously, ESC8 activates autophagy as well as apoptosis. This rare, dual phenomenon is observed only in a few available drug targets. Though results have shown that ESC8 mediates its action through downregulation of mTOR and upregulation of cell death pathways, with autophagic upregulation, further experiments need to be performed to explore the exact cytotoxic mechanism mediated by ESC8. It will be helpful for furthering translational aspect of this interesting molecule.

INTRODUCTION Cell is the structural and functional unit of living organisms and has the ability to divide, differentiate, and die. The balance between these three physiological processes is very important for homeostatic mechanisms of cell. Cells contain different types of organelles (nucleus, mitochondria, endoplasmic reticulum, lysosomes, etc.), which vary in their function. If any organelle malfunctions, cell tries to first normalize the function otherwise altered organelle function persisting in the cell will make the cells either transformed or lead to its death. Cell death is of two types, it may be programmed or nonprogrammed. There are various types of programmed cell deaths, such as autophagy and apoptosis, which are evolutionarily conserved and whose basal levels are required for maintenance of cellular homeostasis. These pathways play crucial roles in development, neurodegeneration, diabetes, cancer, aging, elimination of pathogens, inflammatory diseases, etc.

APOPTOSIS Earlier, the research focused on the role of apoptosis in morphogenesis and development but later the role of apoptosis was also observed in various diseases, such as diabetes, cancer, and aging. Apoptosis is a type-I programmed cell death through which cells are removed from tissues. Apoptosis is characterized by typical morphological and biochemical changes, including cellular and nuclear shrinkage, nuclear condensation, membrane blebbing and cell, and DNA fragmentation (Hiromura et al., 2002). It is a noninflammatory cell death pathway. Mitochondrion is the main organelle involved in apoptosis, even though involvement of endoplasmic reticulum with localized Bcl-2 family proteins is also documented. Herein, caspases play vital role in apoptosis. Usually anticancer agents activate these caspases through the activation of extrinsic or intrinsic pathway (Fulda and Debatin, 2006) (Fig. 14.1A).

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FIGURE 14.1 (A) Extrinsic and intrinisic pathway of apoptosis. (B) Macroautophagy.

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Extrinsic Pathway of Apoptosis It is mainly mediated by death receptors that are members of tumor necrosis factor (TNF) receptor gene super family. There are various death receptors such as Fas receptor (CD95), TNF receptor super family proteins like TNF-related apoptosis inducing ligand receptor (TRAIL), etc. These receptors participate in extrinsic pathway of apoptosis. These receptors contain an extracellular domain (cysteine rich) and intracellular death domain. Binding of ligands or agonists to these death receptors leads to the activation of death-inducing signaling complex (DISC) that further activates the initiator caspases like caspase-8 and caspase-10, which are regulated by cellular FADD-like interleukin-1β converting enzyme-like inhibitory protein. The effector caspase caspase-3 is activated by caspase-8 at the DISC. Two types of pathways are identified based on the concentration of processed/activated caspase-8. In type-1 pathway, which is generally observed in lymphocytes, large amount of caspase-8 that is sufficient to directly activate downstream effector caspases such as caspase-3 is processed. In type-2 pathway, which is generally observed in hepatocytes, small amount of caspase-8 is processed that is insufficient to activate downstream effector caspases and requires amplification of apoptotic signal through mitochondria (Fulda and Debatin, 2006). The effector caspases such as caspase-3 cleave a number of substrates that leads to cellular and biochemical events of apoptosis: loss of cell shape, nuclear shrinkage, and DNA fragmentation.

Intrinsic (Mitochondrial) Pathway of Apoptosis It is the major type of cell death pathway that occurs in cell and mediated by proapoptotic members of Bcl-2 family proteins. The cytotoxic stimuli caused by loss of mitochondrial membrane potential, chemotherapy, and proapoptotic signal–transducing molecules converge on mitochondria and induce the permeabilization of outer mitochondrial membrane (OMM), which is regulated by Bcl-2 family proteins (Fulda and Debatin, 2006). Bcl-2 family proteins are of two types based on their function (proapoptotic—BAX, BAK, and BAD and antiapoptotic—Bcl-2, Bcl-XL, and Mcl-1). Upon disruption of OMM, a number of proteins including cytochrome c, AIF, endonuclease, Smac/DIABLO, and Omi/ HtrA2 (Saelens et al., 2004) are released from mitochondria. The release of cytochrome c causes the activation of caspases in a sequential manner. Cytochrome c acts as cofactor for apoptotic protease activating factor-1 (Apaf-1) function (Li et al., 1997a,b, Kim et al., 2005). In the presence of ATP or deoxy-ATP (d-ATP) cytochrome c binds with Apaf-1 (Liu et al., 1996), which leads to formation of apoptosome that recruits procaspase-9. Except procaspase-9 all known caspases are activated only after processing or proteolytic cleavage (Stennicke et al., 1999). Procaspase-9 undergoes conformational change, forms a dimer (Pop et al., 2006), and becomes activated. The activation of initiator caspases is not enough to cause cell death, so the amplification of this signal requires the activation of effector caspases, such as caspase-3 and caspase-7 (important for cardiac development), which are crucial for apoptosis (Lakhani et al., 2006), through the formation of apoptosome complex that contains cytochrome c-Apaf1-caspase-9. Activated caspase-3 or caspase-7 cleaves the key substrates and consequently leads to the cellular and biochemical events of apoptosis.

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AUTOPHAGY Initially seminal experiments on autophagic cell death were conducted in yeast under nutrient stress (Baba et al., 1994), but later the role of autophagic machinery was also studied in mammalian cells in cancer, neurodegeneration, development, longevity, and heart diseases. Autophagy is upregulated during external stress that is caused due to starvation, hypoxia, infection, oxidative stress and intracellular stress caused by endoplasmic reticulum stress, and gathering of damaged organelle and damaged proteins. Although apoptosis is the main programmed cell death pathway, autophagy also plays an important role in certain situations, but the role of autophagy in cancer cell is still controversial because it leads to both cell survival and cell death. Autophagy is a type-II programmed cell death pathway and it is a self-eating catabolic process that contributes to the maintenance of cellular homeostasis by mobilizing damaged proteins, long-lived proteins, protein complexes, and organelles to lysosomes. Autophagy mainly signifies three important cellular processes, which diverge from each other in their function. These are: macroautophagy (selective or nonspecific sequestration of cellular cargo into autophagosomes.), microautophagy (direct sequestration of cellular components through invaginations in their limiting membrane by lysosomes), and chaperone-mediated autophagy (chaperone-dependent selective and direct translocation of unfolded proteins across the lysosomal membrane without formation of vesicles). Following are few different types of autophagies: aggrephagy (autophagy of aggregated proteins), zymophagy (selective autophagy of secretory granules during pancreatitis), mitophagy (selective autophagy of mitochondria), nucleophagy (selective autophagy of nucleus), pexophagy (selective autophagy of peroxisomes), reticulophagy (degradation of endoplasmic reticulum through autophagy during ER stress). Macroautophagy (autophagy) operates in five different steps: nucleation, expansion or elongation, encapsulation, fusion, and lysis (Fig 14.1B). All these steps follow the same order as mentioned. During nucleation a double-membranous structure is formed which is called phagophore. This lipid-based phagophore elongates, encapsulates and sequesters the cellular cargo, and forms matured spherical autophagosome. The lipid source for the formation of autophagosomes is derived from Golgi apparatus, endoplasmic reticulum, mitochondria, or plasma membrane (Van der Vaart et al., 2010; Hayashi-Nishino et al., 2009; Hailey et al., 2010; Ravikumar et al., 2010). The autophagosome fuses with lysosome directly or fuses with endosomes to form amphisome that further fuses with lysosome to form autolysosome. In lysosomes various enzymes degrade the cellular cargo. After degrading, they are released and recycled back.

Fundamental Mechanism of Autophagosome Construction The machinery of autophagy is mediated by Atg proteins (Mizushima et al., 2011). The Atg proteins are divided into following groups based on their function. 1. The Atg/ULK complex: During starved/nutrient-poor conditions serine/threonine kinase Atg1 (ULK1) complex dissociates from mTOR, and phosphorylates Atg13 and RBICC/FIP200 (homologous to yeast Atg17) (RBI-induced coiled coil), thereby inducing nucleation phase.

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2. Atg9 and its cycling system: It plays a main role in membrane delivery to the preautosomal structure (PAS) and extending phagophore after the induction of autophagosome formation. This complex helps in the recycling of cellular macromolecules such as lipids and proteins. 3. The PI3K complex: It plays a vital role in autophagosome nucleation and exhibits different functions (autophagosome formation, maturation, and lysosomal fusion) depending upon the composition of auxiliary proteins. 4. Two ubiquitin-like (UBL) conjugation systems: It constitutes almost half of the core Atg proteins and plays a vital role in phagophore membrane expansion or elongation. Various stress-responses, hormones, and growth factors activate autophagy. Autophagy is initiated by accumulation of lipids toward the formation of prePAS and proteins such as ULK1 complex, Atg13, and FIP200. Atg9, phosphorylated by ULK1, plays role in the recruitment of vesicles for PAS by interacting with Atg13 and after supplying vesicles to PAS, Atg9 is recycled back. The shuttling of Atg9 to and from is facilitated by Atg27. PAS nucleates to form phagophore, which is facilitated by class-III PI3K complex that consists of Atg14L, Beclin 1, Vps15, and Vps34. This complex generates phosphatidylinositol-3-phosphate that is essential for the recruitment of other Atg proteins. During expansion or elongation stage of autophagosome, membrane progressive reactions of two UBL conjugation systems play an important role. In the (1) UBL system reactions E1-like enzyme Atg7 and E2-like enzyme Atg10 link Atg5 and Atg12. This Atg5-Atg12 complex binds with Atg16 and forms a large complex that leads to the formation of PAS. (2) conjugation system operation Atg4, a protease that mediates microtubule associated LC3 (light chain-3) cleavage at c-terminus forms LC3-I. During initiation of autophagy, LC3-I present in cytoplasm conjugates with phosphatidyl ethanolamine (PE) mediated by an E1-like enzyme Atg7 and E2-like Atg3. This lipidated LC3 called LC3-II is selectively recruited to autophagosomal membrane in punctate format. When autophagosome fuses with lysosome mediated by SNAREs and RAB7, it forms autolysosome. LC3-II exists on autophagosomal membrane even after fusion with lysosomes. In autolysosomes the enzymes of lysosomes degrade LC-II-associated autophagosomal cargo. Thus, LC3-II turnover by lysosomal protease serves as a marker for autophagy. After digestion by lysosomal enzymes, the cellular components are recycled back (Feng et al., 2014).

CROSS TALK BETWEEN APOPTOSIS AND AUTOPHAGY Apoptosis and autophagy not only allows degradation but also involves in the recycling of cellular components. Apoptosis-mediated cellular homeostasis is executed through controlled elimination of cells, maintenance of cell numbers, and their proliferation. Autophagy-mediated cellular homeostasis is also performed through the breakdown and reformation of organelles and other components. Autophagy and apoptosis can be assessed simultaneously by using multispectral imaging cytometry (De la Calle et al., 2011). By identifying the link between autophagy and apoptosis, it will be easy to find common molecular factor regulating both these pathways. As a result, it will be possible to treat various diseases, as in most of the chemotherapeutic interventions, apoptosis and autophagy are the

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main targets. Some apoptotic proteins play a role in autophagy, while some autophagic proteins play a role in apoptosis. Even though the mechanisms involved in this regulation are not clearly known, the available evidence proves that autophagy and apoptosis are interconnected with each other. For convenience the cross talk between autophagy and apoptosis is divided as follows.

Intrinsic Apoptosis–Autophagy Chen et al. (2009) showed that PKCδ/JNK is activated during early stages of hypoxia. This activates caspse-3 and mediates phosphorylation of Bcl-2 and dissociation of Bcl-2/ Beclin 1 complex (Wei et al., 2008). Earlier research showed that JNK-mediated Bcl-2 phosphorylation interferes with its binding to BAX (through their BH3 domains), but recently it was demonstrated that JNK-mediated Bcl-2 phosphorylation interferes with its binding to proautophagic protein Beclin 1 (mammalian ortholog of yeast Atg6). According to this model, initially autophagy is triggered (to promote cell survival) by the disruption of Bcl-2Beclin due to rapid JNK-mediated Bcl-2 phosphorylation. At certain point when autophagy is no longer able to keep the cell survive, Bcl-2 phosphorylation might serve to inactivate antiapoptotic role (Wei et al., 2008). NAF-1 (nutrient-deprivation autophagy factor-1) binds to Bcl-2 at the endoplasmic reticulum. This interaction is BH3 independent. NAF-1 is a component of IP3 receptor (inositol-1,4,5 triphosphate receptor) complex that contributes to the interaction of Beclin 1 with Bcl-2 and is a prerequisite for Bcl-2 to antagonize Beclin 1–mediated autophagy (Maiuri et al., 2010). Autophagy-related gene 12 (ATG12) promotes apoptosis by binding to antiapoptotic members of the Bcl-2 family proteins, which was proved by RNAi screening (Chonghaile and Letai, 2011). In the TrkA overexpressing cells, JNK-calpain pathway might be playing a role in the induction of autophagy and apoptosis (Dadakhujaev et al., 2009). BCL2L11 (Bim) interaction with BECN (Beclin 1) facilitated by DYNL1 (dynein light chain1) was discovered recently. During starved conditions, Bim is phosphorylated by MAPK8/JNK and allows the dissociation of Bim and BECN1 (which are interacted through their BH3 domain) by abolishing the Bim-DYNL1 interaction, thereby enhancing autophagic inhibition. This finding reveals a novel role of BIM beyond its role in apoptosis (Luo and Rubinsztein, 2013). Another study has mentioned that autophagy and apoptosis gene cascade play redundant (shared) role during Caenorhabditis elegans development (Borsos et al., 2011). Caspase-3 cleaves Atg4D, which participates in autophagy at DEVD63K during apoptosis. Cleaved Atg4D gains GABARAP-L1 priming/delipidating activity and is highly cytotoxic and leads to autophagy (Betin and Lane, 2009). The receptor for advanced glycation end products (RAGE) that plays an important role in various diseases increases autophagy and decreases apoptosis via ROS signaling mediated through NF-κβ (Kang et al., 2011).

Extrinsic Apoptosis–Autophagy Sequestration and breakdown of active caspase-8 by autophagy is mediated by TRAIL (Hou et al., 2010). FLIP is a major antiapoptotic regulator that suppresses TNF-α-, FAS-L-, and TRAIL-induced apoptosis. FLIP not only forms apoptosis inhibitory complex by binding with FADD, caspase-8 or caspase-10, and TRAIL receptor 5 (DR5) but also interacts with the E2-like enzyme Atg3 and serves as antiautophagic factor (Lee et al., 2009).

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Autophagosomal membrane may serve as a platform for DISC formation that activates caspase-8 and initiates caspase-8/caspase-3 cascade (Young et al., 2012).

BREAST CANCER Cancer is triggered by misbehavior of a normal cell that leads to uncontrolled proliferation. Cancer is caused by several reasons: they may be internal (that are caused due to hormones, gene loss-of–function, or gain-of-function mutations that are acquired or hereditary, due to increased expression of oncogenic pathways or decreased expression of tumor suppressing pathways) or external (caused due to radiations, viruses, tobacco and alcohol consumption, infections, food habits, environmental pollutants). Cancers of different types are based on which organs are affected: lung cancer, breast cancer, colon cancer, ovarian cancer, prostate cancer. Cancers are simply divided into two main categories: sarcoma (originates from mesenchymal cells) and carcinoma (originates from epithelial cells). Steroid hormones play vital role in the development of most types of cancers. They may be membrane hormone receptors, cytoplasmic receptors, and nuclear hormone receptors. Mostly steroid hormones have receptors inside the nucleus. There are certain steroid hormones which have receptors in the cytoplasm, but after binding with ligand or hormone, they are translocated into nucleus. Breast cancer is widespread in female population and rarely observed in males. After lung cancer, breast cancer ranks second most common cancer in women. According to information provided by American Cancer Society 40,730 breast cancer deaths were expected in 2015 in US population. Breast cancer is characterized by the presence of lump or mass of tissue in breast. Function of mammary stem cells is mainly dependent on steroid hormones. Breast cancer is divided into different groups based on the presence or absence of “three” hormone receptors—estrogen receptor, progesterone receptor, human epidermal growth factor-2. For example, breast cancer cell lines can be subtyped into ER-positive (MCF-7) or ER-negative (MDA-MB-231) based on the presence of ER. The breast cancer in which these three hormones are nonfunctional, mutated, or absent is called triple-negative breast cancer (TNBC). Cancer treatment can be carried out by diminishing or inhibiting the snow-balling cell proliferation and enhancing the cell death. So induction of cell death and inhibition of cell multiplication are the main principles of cancer therapy. Various pathways regulate cell death and cell proliferation in cancer cell. Among them PI3K-AKT-mTOR signaling pathway plays a pivotal role.

PI3K-AKT-mTOR SIGNALING PATHWAY Here, we are discussing the ER-mediated action of PI3K-AKT-mTOR signaling pathway. In breast cancer cells due to loss of control over metabolism, various metabolic pathways are altered. Among them, PI3K-AKT-mTOR signaling pathway that is investigated extensively plays a key role. ER shows action by two mechanisms: either by binding to ER which further binds to estrogen receptor element (ERE) inside the nucleus or by mediating the activation of signal

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FIGURE 14.2 Estrogen signaling via PI3K-AKT-mTOR signaling pathway. Estrogens mediate their mode of action either by binding to their receptors (ER or GPER) or by directly interacting with PI3K. When estrogens bind with ER, it enters into nucleus and binds with ERE and regulates the transcription of specific genes.

transduction pathways in cytoplasm (Guo et al., 2006) (Fig. 14.2A). There are three different classes of PI3Ks: PI3K class-I, PI3K class-II, and PI3K class-III. Class-I PI3K consists of two subunits, the regulatory subunit (p85) and catalytic subunit (p110). Generally, PI3K (phosphatidylinositol-3-kinase) is activated by growth factors, such as platelet-derived growth factor and insulin-like growth factor (Cantley, 2002), that activate receptor tyrosine kinase. FAK (focal adhesion kinase) involved in cell adhesion and metastasis is overexpressed in breast cancer cells and mediates signaling through MAP kinase. This leads to activation of PI3K which, in turn, is involved in cell survival by activating AKT (Schlaepfer et al., 1999); but

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estrogen-mediated activation of PI3K in a ligand-dependent manner is reported only in few studies which represent the significance of ER interaction with PI3K and activation of PI3KAKT-mTOR signaling pathway (Simoncini et al., 2000). PI3K signaling pathway is activated either in cytoplasm or in nucleus and is involved in tumorigenesis and cancer development (Davis et al., 2015). But most of the studies are carried out on cytoplasmic PI3K pathway. Some studies state that PI3K is overexpressed in cancer cells due to mutation in PIK3CA gene (Janku et al., 2012) located in chromosome 3q26.3. PI3K converts PIP2 (phosphatidylinositol3,4-bisphosphate) into PIP3 (phosphatidylinositol-3,4,5-triphosphate) that acts as secondary messenger for signaling pathway (Cantley, 2002). This conversion is also regulated by PTEN (phosphatase and tensin homolog deleted on chromosome 10), which is involved in dephosphorylation of PIP3 to PIP2 (Castellino and Durden, 2007). In the presence of PTEN, AKT activation is inhibited. PTEN regulates cell growth and apoptosis by controlling AKT activation. Loss or mutation of PTEN is observed in most of the tumors (Li et al., 1997a,b). AKT or protein kinase B when binds to PIP3 will undergo phosphorylation at Thr308 by PDK1and phosphorylation at Ser473 by PDK2 or other kinases (Chan et al., 1999). There are three types of AKTs, distributed in cytoplasm and nucleus and play a key role in cell survival and cell proliferation, but the mechanism involved in the AKT activation and localization is not clear (Santi and Lee, 2010). AKT characterized as an oncogene is one of the client proteins of HSP90 and forms a complex with HSP90 that plays an important role in cancer provocation through glucocorticoid receptor (GR) (Sato et al., 2000). In cancer cells TSC-1 is unable to form a complex with TSC-2 as AKT phosphorylates TSC-2. Phosphorylated TSC-2 is unable to inhibit mTOR (mammalian target of rapamycin) activation which is mediated through Rheb (Ras homolog enriched in brain) (Huang and Manning, 2009). In normal cells TSC-1 forms a complex with TSC-2 and inhibits Rheb so that mTOR is also inhibited, but in cancer cells constitutive AKT activation inhibits TSC-2 activation and leads to mTOR activation. mTOR is the downstream effector of AKT in PI3K-AKT-mTOR signaling pathway (Laplante and Sabatini, 2012). There are two complexes of mTOR; mTORC1 and mTORC2, which are defined, based on their interaction with accessory proteins like raptor, mLST8, PRAS40 and rictor, mSIN, PROTOR proteins, respectively, mTORC1 is mainly regulated by nutrients and amino acids but mTORC2 is primarly activated by growth factors (Menon and Manning, 2008). mTOR complex shows its action by regulating the downstream molecules, p70S6k and 4E-BP1 in the signaling pathway, which is further involved in the regulation of protein synthesis required for cell division, differentiation, and cell death (Li et al., 2008). mTOR complex also plays an important role in protein transport, ribosomal biogenesis, apoptosis, autophagy, cytoskeletal association, and protein breakdown by acting on its substrates, AKT, SGK, and PKC (Zoncu et al., 2011).

PI3K-AKT-mTOR Signaling Cell Death BAD, a proapoptotic protein, exerts its apoptotic functions by forming complex and inhibiting Bcl-XL, an antiapoptotic protein. IL-3 activates AKT in a PI3K-dependent manner and is involved in the inhibition of apoptosis through the phosphorylation of BAD, and thus increases cell survival rate (Zhang et al., 2011). AKT promotes cell survival by inhibiting apoptosis through the phosphorylation of proteins such as BAD, caspase-9 involved in apoptosis (Cardone et al., 1998). AKT also inhibits apoptosis by involving in

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the phosphorylation of transcription factors such as ASK1 (Kim et al., 2001) and TR3 (Chen et al., 2008). AKT keeps various Bcl-2 family proteins (PUMA, BIM, BAD) inactive, which repress the growth factor signaling. GSK3β acts at the downstream of PP2A and PI3K signaling pathway and is involved in ceramide-induced apoptosis. GSK3β phosphorylates various proteins including BAX (Linseman et al., 2004) and plays an important role in apoptosis and cell survival. SNAIL, a transcription factor, is also one of the substrates for GSK3β that is involved in epithelial–mesenchymal transition (EMT) (Zhou et al., 2004). AKT phosphorylates various transcription factors (FOXO3) and causes their association with 14-3-3. This leads to their sequestration and inhibition of apoptotic effect. 14-3-3 is phosphorylated by JNK and dissociates from apoptotic proteins thereby antagonizing effect of AKT signaling (Sunayama et al., 2005). O-linked N-acetyl glucosamine glycosylation enhances apoptosis by inhibiting phosphorylation/activation of AKT and BAD (Shi et al., 2015). PH domain leucine-rich repeat protein phosphatase dephosphorylates AKT and triggers apoptosis and inhibits tumor growth (Lv et al., 2015). mTOR-mediated blockade of apoptosis is not fully understood. Mcl-1 is a prosurvival Bcl-2 family protein whose translation is stimulated by mTORC1. It contributes to cell survival (Mills et al., 2008). Mcl-1 interacts with BAK and inhibits its apoptotic activity. Noxa, a BH3-only domain protein, is able to disrupt the interaction of Mcl-1 and BAK and results in the ubiquitination of Mcl-1, thereby promoting apoptosis. Mcl-1 also interacts with Bim and thwarts the translocation of Bax into mitochondria (Harada et al., 2004). When Bim is phosphorylated by AKT, Bim undergoes ubiquitination and is degraded in proteosomal complex (Coloff et al., 2011). mTOR also induces the translation of FLIPs protein that blocks caspase-8 activation which is at the downstream of TRAIL (Zhao et al., 2013). mTOR complex shows its action on apoptosis by acting on p53, p27, p21, and c-MYC (Faivre et al., 2006). Beclin 1 interacts with class III PI3K (Vps34) and plays an important role in autophagosome initiation (Funderburk et al., 2010). mTORC1 is the central player of autophagic mechanism, and autophagy is negatively regulated by mTORC1. Amino acids regulate mTORC1 through Rag GTPases (Sancak et al., 2008). mTORC1 is recruited on lysosomal membrane by activated GTPases and plays an important role in autophagy in neonates. During starved conditions or nutrient-limited conditions, AMP-activated kinase (AMPK) is activated by high amount of AMP/ATP and LKB1. Activated AMPK stimulates TSC1/2 complex through phosphorylation and suppresses mTORC1 that leads to the activation of autophagy (Inoki et al., 2005). If mTOR is activated by PI3K-AKT signaling, it phosphorylates autophagic protein complex ULK1/2 and inhibits autophagy (Alers et al., 2012). AKT phosphorylates and inhibits autophagy by instigating the interaction of Beclin 1 with 14-3-3 (Wang et al., 2012). DEPTOR (DEP domain containing mTOR-interacting protein), which acts as an inhibitor of mTORC1, induces autophagy (Zhao et al., 2011). IKK activated by insulin and TNF-α phosphorylates TSC1/2 complex results in the activation of mTOR, and finally leads to autophagy in an NF-κB independent manner (Dan and Baldwin, 2008).

PI3K-AKT-mTOR Pathway Cell Proliferation/Cell Cycle Mitogens, growth factors, hormones, and cytokines activate mTOR and other kinases and stimulate the separation of 4EBP from eIF4E (Bjornsti and Houghton, 2004). Hence, free eIF4E is able to form a multisubunit eIF4F complex that contains eIF4A, eIF4B, eIF4G and

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enables cap-dependent translation. This leads to a series of events enhancing the translation of cyclin D1 and MYC mRNA, which is required for G1–S phase transition in many cancers. An opposite result is observed under starved condition. AKT in activated state is able to phosphorylate and inhibit GSK3β but in inactivated state of AKT, GSK3β phosphorylates several proteins such as cyclin D1, MYC (Luo et al., 2003), Cdc2 (cell division cycle protein 2, which is homolog of cyclin-dependent kinase1) that are involved in cell cycle. Cdc2 regulates cell cycle and also promotes apoptosis by phosphorylating BAD (Konishi et al., 2002). When BAD is phosphorylated by Cdc2, AKT is unable to phosphorylate BAD as the phosphorylating site for AKT is not available. As discussed earlier, AKT is activated by phosphorylation at several of its amino acid residues. Among them S477 and T479 are phosphorylated by cell cycle regulator cyclin A (also called cyclin-dependent kinase 2) and mTORC2 based on various physiological conditions.

P53-mTOR Pathway Cell Death and Cell Survival P53 is activated during DNA damage and acts as a tumor suppressor. The regulation of apoptosis by permeabilization of OMM through activating proapoptotic proteins (BAX and BAK), autophagy (either by transactivating genes such as DRAM and Sestrins or by any other unclear mechanism), and cell cycle by p53 occur independent of one another. MDM2 is involved in the regulation and degradation of p53. AKT has the ability to phosphorylate MDM2. Phosphorylated MDM2 provokes p53 for its degradation. RB (retinoblastoma) binds with MDM2 and acts as a positive regulator of p53-mediated apoptosis and cell cycle (Hsieh et al., 1999). WISP1 participates in WNT pathway which is another regulator of p53 and acts through AKT (Su et al., 2002). PTEN and p53 mutually depend on each other. PTEN protects p53 from MDM2-mediated proteasomal degradation; in return, p53 boosts the transcription of PTEN (Trotman and Pandolfi, 2003). Loss of p53 and CKIα leads to the activation of a set of genes (PSIS), which is believed to be involved in tumor invasiveness and p21 suppresses PSIS in cell cycle in an independent manner (Elyada et al., 2011). Targeted Chemotherapy-Breast Cancer-mTOR Pathway Cell Death There are various therapies such as radiation therapy, chemotherapy, gene therapy and surgery for controlling breast cancer. Targeted therapy is a type of treatment for breast cancer in which a drug is particularly targeted to cancer cells only. In most of the chemotherapeutic interventions, apoptosis and autophagy are the main targets in cancer cells. PI3K-AKT-mTOR route is central to most of the pathways that are altered in cancer and this route regulates autophagy and apoptosis. Hence understanding the molecular mechanisms that regulate autophagy and apoptosis in response to anticancer chemotherapy provides new approaches to develop molecularly targeted treatments for fighting breast cancer. Even though various PI3K-AKT-mTOR pathway inhibitors exist, a cationic lipid that act as an anticancer agent via this pathway and induce apoptosis and autophagy is unique in our study which is discussed here under. Small Molecular–Weight Cationic Lipids as Anticancer Agents The cellular membrane is negatively charged and hence is able to attract positively charged cationic lipids that have easy access into the cell. This is the basis of developing cationic lipid based liposomal gene delivery systems (Karmali and Chaudhuri 2007).

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In this context we are going to discuss the development of a novel class of molecules that are actually cationic lipid conjugates of various receptor ligands, synthetic and natural. These were initially designed and synthesized in our laboratory for targeted gene delivery but are found to act as anticancer agents. On chemically conjugating (instead of associating in liposomal formulations) C-8 long chain cationic lipid with specific ligands, we observed selective anticancer effect. From this, we presumed that instead of associating one conjugate long-chain cationic lipid with a particular molecule or ligand with a spacer in between, the resulting molecule acts as a targeting ligand for a particular receptor expressed on cancer cell or acts as a selective anticancer agent. Hence, we synthesized molecules that target sigma receptor (SR) (HPC8), GR (DX8 and HYC16) and ER (ESC8), respectively. HPC8 was synthesized by conjugating C-8 cationic lipid long chain with haloperidol, an antipsychotic drug and ligand for SR (Pal et al., 2011). HPC8 acted as an anticancer agent by downregulating AKT activation. DX8 was synthesized by conjugating C-8 cationic lipid long chain with Dexamethasone, a synthetic GR ligand. DX8 acted by downregulating JAK-STAT pathway (Sau and Banerjee, 2014). Similarly, HYC16 was the C-16 cationic long-chain derivative of GR natural ligand, hydrocortisone. HYC16 showed potent and selective antiangiogenic and apoptosis inducing property in melanoma tumor (Rathore et al., 2015). ESC8, A C-8 Cationic Lipid Containing Estradiol as an Anticancer Agent ESC8 was synthesized by conjugating C-8 cationic lipid long chain to 17β-estradiol through a spacer at its 17 position (Fig. 14.3A and 14.3B). 17β-estradiol acts as a ligand for ER that is highly expressed in breast cancer. ESC8 molecule functioned as anticancer agent by selectively acting as an inhibitor for mTOR downstream pathway. To our surprise, ESC8 acted not only against ER-positive cancer cells but also against ER-negative cancer cells (Sinha et al. 2011).

ESC8 Is a Potent Anticancer Agent Against ER-Positive and ER-Negative Cancer Cells After synthesis of ESC8, we tested its effect on breast cancer cells (ER-positive and ER-negative), and in normal cells, and found that ESC8 specifically acts on cancer cells. We compared ESC8 effect with already existing breast cancer drugs. These drugs are 2-methoxy estradiol, tamoxifen, and epirubicin. First drug is an antiestrogen and are estrogen homologs called estrologs; and the latter two drugs are nonestrogenic breast cancer drugs. These are treated to ER-positive (MCF-7) and ER-negative (MDA-MB-231) breast cancer cells (Fig. 14.3C and D). Our data clearly indicate that ESC8 displays efficient killing. Earlier literature suggests that molecules such as tamoxifen and Faslodex (which contain ES moiety) function through antagonizing ER in ER-positive cells, but our results demonstrate that estrologs that are derived from estrogen moiety (ESC8) not only are specific to ER-positive cells but also act against ER-negative cells. So, one can question if they are acting only via ER! The answer is yes for ER-positive breast cancer cells because when cells (MCF-7 and MDA-MB-231) are pretreated with ICI182780 (an ER antagonist) before the treatment with ESC8, the anticancer effect was abrogated in MCF-7 cells (data not shown). Now, we can pose one more question: how is ESC8 acting on MDA-MB-231 cells? As acknowledged in literature, estrogen also acts via GPER (G-protein-coupled estrogen receptor). Our ESC8 might show its anticancer effects through GPER. ESC8-mediated killing of MDA-MB-231

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FIGURE 14.3 Structure and anticancer effect of ESC8 against breast cancer cell lines. (A) Structural details of ESC8. (B) 48 h treatment of MCF-7 and MDA-MB-231 cells with ES, C-8 long chain control, ES plus C-8 control, and ESC8 at 10 mmol/L concentration (of every component) followed by MTT assay for the determination of cell viability. (C) MTT assay result of MCF-7 with ESC8, 2-methoxy estradiol, 4-hydroxy tamoxifen, epirubicin, tamoxifen at 1.25, 2.5, 5.0, and 10.0 µmol/L concentrations. (D) MTT assay result of MDA-MB-231 cells with ESC8, 2-methoxy estradiol, 4-hydroxy tamoxifen, epirubicin, tamoxifen at 1.25, 2.5, 5.0, and 10.0 µmol/L concentrations. Reproduced with permission from AACR (USA).

cells provoked us to investigate the in-depth mechanisms that are involved in cell death of ER-positive and ER-negative cancer cells.

ESC8 Mediates Intrinsic Apoptotic Pathway in Breast Cancer Cell Lines ●

Strategy-1: Staining As apoptosis is the main cell death mechanism linked to cancer therapy, we performed annexin-V and PI binding assay in MCF-7 and MDA-MB-231 cells after ESC8 treatment. The results showed apoptosis induction in both cells. Apoptosis induction was also confirmed by DAPI staining. DAPI staining showed shrinkage of cytoplasm and nucleus in these cells. These results made us question the pathway involved in apoptosis of these cells (Fig. 14.4A).

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FIGURE 14.4 Apoptophagy (apoptosis and autophagy) induction by ESC8 treatment in MDA-MB-231 cells. (A) DAPI staining of normal and ESC8 treated MDA-MB-231 cells showing apoptosis induction in treated cells at 5 µM concentration. (B) Immunoblot of MDA-MB-231 showing upregulation of Bax to Bcl-2 ratio at 10 µmol/L dose of ESC8 and increase in cytochrome c level at 5 and 10 µmol/L after 16 h treatment with ESC8. (C) Western blot of caspase-9 and caspase-3 shows that 1 and 5 µmol/L doses of ESC8 is sufficient for the activation of caspase-9 and caspase-3 after 16 h treatment. (D) ESC8 treatment at 5 μM concentration-induced autophagic vesicle formation in MDA-MB-231 cells which is proved by monodansylcadaverine labeling. (E) Western blot analysis says that LC3B-II significantly increased even at 1 μmol/L dosage of ESC8, but there is no significant increase in the level of Atg5Atg12 and Beclin 1. (F) Autophagic flux determination with ESC8 treatment in MDA-MB-231 cells in the presence and absence of pepstatin-A and E64D. (G) ESC8 (5 µmol/L)-mediated autophagic induction there by cell killing was significantly reduced upon treatment with Atg-5 si-RNA or knockdown of Atg-5. (H) Western blot analysis of LC3B-II and Atg5-Atg12 complex upon treatment of MDA-MB-231 cells with Atg-5 si-RNA followed by ESC8 treatment (5 µmol/L). Here β-actin is used as a loading control. Reproduced with permission from AACR (USA). II. ROLE IN DISEASE

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Strategy-2: Immunoblotting As most of the anticancer agents trigger intrinsic pathway of apoptosis, we checked the expression level of pro- and antiapoptotic proteins of Bcl-2 family, as the ratios of pro- and antiapoptotic protein levels determine the upregulation or downregulation of apoptosis. The ratio of BAX to Bcl-2 indicates that increased ratio of BAX to Bcl-2 with increased concentration of ESC8 may lead to the initiation of OMM permeabilization that possibly instigates apoptosis. We expanded our study for the analysis of other proteins of apoptosis. As stated in literature, increased level of cytochrome c indicates the manifestation of apoptosis, and increased concentration of ESC8 triggers the increase of cytochrome c. These results reveal that increased level of BAX is the cause for increased level of cytochrome c following ESC8 treatment (Fig. 14.4B). The role of caspases in apoptosis was also seen with the treatment ESC8. As we increased the concentration of ESC8, the expression level of activated caspase-9 (instigator caspase), activated caspase-3 (amplifier of apoptotic signal) also increased because of increased cytochrome c level in the cytoplasm (Fig. 14.4C). These results indicate that the intrinsic pathway of apoptosis is the main pathway of ESC8-mediated cell death.

Induction of Autophagic Cell Death by ESC8 Although apoptosis is the main programmed cell death pathway, autophagy also plays an important role in certain situations. There are several studies that discuss the role of autophagy induction in cancer cells during chemotherapy, but the role of induction of autophagy in cancer cells is still a debate because of its dual role. ●

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Strategy-1: Staining MDC staining is a type of technique that is convenient to detect autophagic vesicle formation. During autophagic vesicle maturation, MDC binds and stains autophagic vesicles. Therefore MDC staining serves as a specific marker of autophagolysosome formation. With ESC8 treatment, MDC staining is clearly observed in fluorescent microscopy indicating the induction of autolysosome formation (Fig. 14.4D). Strategy-2: Immunoblotting Autophagy activation results in the formation of phagophore that grows and expands to form a double-membranous structure called autophagosome. This process requires a group of proteins called Atg (autophagy-related) proteins. Among them Atg5-Atg12 and Atg8 (LC3) ubiquitin-like complexes are important for fine tuning of autophagosome expansion. The Atg7 and Atg10, E1-like, and E2-like autophagic proteins are involved in the covalent linking of Atg12 with Atg5. During autophagic process, LC3 is converted to LC3-I. LC3-I conjugates to phosphatidylethanolamine and forms LC3-II that recruits in autophagosomal membrane. LC3-I to LC3-II conversion acts as a biomarker for the incidence of autophagy. When MDA-MB-231 cells are treated with increasing concentrations of ESC8, the level of Atg5-Atg12 complex increases, which can be detected by Western blotting. ESC8 treatment also induces LC3-II formation (Fig. 14.4E). Strategy-3: Inhibitor treatment After the formation of LC3-II during the autophagic late stages, it undergoes degradation in lysosomes. In the presence of lysosomal protease inhibitor, LC3-II is not degraded by lysosomal proteases. Hence the amount of LC3-II is increased in the lysosomes.

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When MDA-MB-231 cells are treated with ESC8 in the presence or absence of pepstatin-A (a lysosomal protease inhibitor), there is clearly an increase in the amount of LC3-II in the presence of pepstatin-A. It means that increased amount of LC3-II is due to pepstatin-A, and it also suggests that the autophagic reaction is activated by ESC8 (Fig. 14.4F). Strategy-4: siRNA treatment The siRNA technology is widely used to allow siRNA to target a particular m-RNA of a specific protein. This technique is useful for understanding the exact function of a particular targeted protein. siRNA is the RNA sequence that targets, and binds with m-RNA and mediates degradation of m-RNA. When siRNA for Atg5 is added to cell lines, it leads to the inhibition of autophagy as Atg5 protein is not formed. It is known that ESC8 induces autophagy, but it is not sure that the autophagic induction by ESC8 leads to cell death in MDA-MB-231 cells. Before the treatment with ESC8, MDA-MB-231 cells are pretreated with siRNA. After this treatment, MTT assay is performed to assess cell viability and the levels of LC3-II and Atg5-Atg12 complex expression is observed. Due to inhibition of Atg5 protein expression, the level of Atg5Atg12 and LC3-II is also decreased and the MTT results show that the cell viability is more in siRNA plus ESC8 treatment when compared with ESC8-treatment alone (Fig. 14.4G and 14.4H). These results prove the induction of ESC8 treatment–mediated autophagic cell death in MDA-MB231 cells.

ESC8-PI3K-AKT-mTOR Pathway As described earlier, the PI3K-AKT-mTOR pathway is the main pathway that plays a vital role in tumorigenesis. As also evidenced earlier, estrogen shows its activities in both ER-dependent and PI3K-AKT-mTOR-dependent pathways, so we searched for what could be the possible mechanism of anticancer action of ESC8, especially in ER-negative breast cancer cells. As ESC8 acted even in ER-negative cells, one can expect the possibility of involvement of PI3K-AKT-mTOR pathway. So, we proceeded through Western blot to check the expression of PI3K, AKT, mTOR. To our surprise, we found that ESC8 showed its anticancer effect similar to rapamycin, i.e., by inhibiting mTOR phosphorylation but not by interacting with PI3K or AKT. We also observed decreased level of p-p70s6K, which is a consequence of p-mTOR inhibition as p70s6K is the target for mTOR (Fig. 14.5A).

ESC8 Treatment Leads to Apoptosis and Tumor Regression in Mouse Tumor Model To confirm the anticancer effect in vivo, Balb/C SCID mice were injected orthotopically in mammary pad with MDA-MB-231 cells, and when the tumor reached ~30–40 mm3 for one batch and 130 mm3 for another batch, ESC8 (10 mg/kg/mice) was administered intraperitoneally. Even with limited number of ESC8 injections (2 alternate day injections for 30- to 40-mm3 tumors and 4 alternate day injections for 130-mm3 tumors) we can clearly observe the regression in tumor volume (Fig. 14.5B). To confirm the occurrence of apoptosis in ESC8-treated tumors TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling) assay was performed. This histological study clearly showed a significant increase in ESC8-treated group (Fig. 14.5C and D).

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FIGURE 14.5 Cytotoxic effect of ESC8 in breast cancer cells by affecting PI3K-AKT-mTOR pathway and in vivo confirmation of tumor regression induced by ESC8. (A) 1 µmol/L ESC8 treatment in MDA-MB-231 cells lead to the downregulation of p-mTOR (2448), p70S6K (thr-389), and the upregulation of p-AKT at 10 µmol/L dose determined by Western blot analysis. Here β-actin is used as a loading control. (B) ESC8 and 5% glucose (control) was administered (2 injections) intraperitoneally when the tumor volume is 30 mm3 and in second group ESC8 was administered (4 injections) when the tumor reached 130 mm3. In both cases ESC8 dose administered is 10 mg/kg/mice. (C) TUNEL assay of control (5% glucose treated) and ESC8-treated groups shows that more number of TUNEL-positive nuclei in treated group. (D) Microscopic observation after TUNEL assay in which 10 randomly selected microscopic fields observed for TUNEL-positive cells in bot control (received 5% glucose) and ESC8-treated (administered 10 mg/kg/mice of ESC8 drug) group. ESC8 treatment leads to the formation of significant number of apoptotic cells. Reproduced with permission from AACR (USA).

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DISCUSSION Breast cancer is the leading cancer in women population. Targeted chemotherapy for breast cancer mainly targets three main hormone receptors that play important role in various types of breast cancers including TNBC. The available drugs have become ineffective because of their side effects and their chemoresistance. The existing challenge is to synthesize a drug that should act on cancer cells at any stage and should show minimal or no effect on normal cells. We synthesized cationic lipid conjugates, DX8, HPC8, and ESC8 that targets GR, SR, and ER, respectively. Among them, ESC8 is synthesized by conjugating C-8 long chain to estradiol, a natural ligand for ER. Based on structural analysis, one can suspect that ESC8 can act in ER-positive cells. However unexpectedly, ESC8 acted even on ER-negative cells. Comparative analysis of ESC8 with already existing estrogen antagonists (tamoxifen, faslodex) shows that it acts only on ER-positive cells. It is concluded that ESC8 is better in its action than tamoxifen, or faslodex. Even though it is not clear, based on the existing evidence one can suspect that at least in ER-positive cells, ESC8 showed its action by binding to ER that further binds to ERE and leads to DNA damage or by simple ER-antagonism. However, it not clear how ESC8 acted on ER-negative cells. Existing evidence suggests that estradiol shows its action by interacting with PI3K. So, more experiments in ER-negative cells revealed that ESC8 mediates its action through PI3K-AKTmTOR pathway, but whether ESC8 interacted with PI3K is not known. Here the outcomes show that ESC8 acted against breast cancer through downregulation of mTOR, which is a target of rapamycin and upregulated p-AKT; this, however, warrants further investigation. Hence, from these results it is clear that ESC8 showed similar mode of action as that by rapamycin. Further investigation showed clearly that ESC8 induced apoptosis in both ER-positive and ER-negative cells. Although we are experimenting with both types of cells, we are more interested in MDA-MB-231 cells as they are ER-negative. The experiments with MDA-MB-231 revealed that ESC8-induced intrinsic pathway of apoptosis in these cells, which was confirmed by elevated levels of caspase-9 and caspase-3. ESC8 also induced autophagy, which is clear by LC3-II formation. Atg5 siRNA experimentation revealed that ESC8-mediated autophagic induction is not prosurvival. Based on these results we can suggest that ESC8, with inclination to induce autophagy, in combination with AKT inhibitor is the better option for targeting breast cancer. It is concluded that ESC8, in contrast to existing estrogenic molecules, is unique in its structure (as it is synthesized by conjugation of estradiol with C-8 long chain) and functions (efficiently against both ER-positive and ER-negative breast cancers). These results offer promising scope to treat breast cancer at any stage of malignancy by coinduction of apoptophagy (apoptosis and autophagy) using a single drug–based targeted chemotherapy.

Acknowledgment S.J. thanks Council of Scientific and Industrial Research (CSIR), Govt. of India for his PhD research fellowship, and R.B. thanks CSIR Network Project Grants (CSC0302 and BSC0123) and CSIR Young Scientist Research Project grant for his research supports.

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15 Intestinal Autophagy Defends Against Salmonella Infection Thomas A. Parker and Kailiang Jia O U T L I N E Introduction 291 Autophagy 292 Salmonella 293 Invasion of Salmonella Into Intestinal Epithelium Cells

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Abstract

Since the 1980’s accumulating evidence has shown that autophagy, an evolutionarily conserved lysosomal degradation pathway, is an essential component in both innate and adaptive immunity. Moreover a complex interplay exists between autophagy-mediated resistance and pathogen virulence factors that attempt to subvert autophagic machinery. Investigations into Salmonella infection have revealed that autophagy in host intestinal epithelial cells is crucial to the restriction of intracellular bacterial survival and replication. This review gives a brief summary of the mechanisms of autophagy and Salmonella invasion with an emphasis on the role of intestinal autophagy in defending against Salmonella infection.

INTRODUCTION Multifaceted adaptation pathways have evolved in eukaryotic organisms to rectify homeostatic disruption triggered by external environmental changes. Among the key processes utilized by eukaryotic organisms to maintain homeostasis is a catabolic pathway known as autophagy (Kroemer et al., 2010). Autophagy is a process by which cytoplasmic organelles and cytosolic components are recycled via the lysosomal degradation pathway.


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Dysregulation of autophagy by systemic or tissue-specific deletion of autophagy-related genes (ATG) have produced multiple human disease–like phenotypes in animal models (Jiang and Mizushima, 2014), including cancer, inflammatory disorders, metabolic disorders, and aging (Choi et al., 2013). Furthermore, it has been widely reported that autophagy plays a critical role in both innate and adaptive immune defense mechanisms against viral, bacterial, and parasitic infections (Choy and Roy, 2013; Deretic, 2011; Orvedahl and Levine, 2009). Autophagy has been shown to participate in nearly all aspects of immunity. It can function as an effector downstream of immunity receptors including Toll-like receptors (TLRs), Nod-like receptors, RIG-I-like receptors, and damage-associated molecular patterns. Autophagy is also involved in MHC II presentation of cytoplasmic self or foreign antigens to activate the adaptive immune response (Deretic, 2011; Orvedahl and Levine, 2009). Recent evidence reveals that autophagy-mediated immune responses play a role in the pathogenesis of human autoimmune disorders. Genomewide association screens and integrated system-level approaches have linked polymorphisms in ATG genes expressed in intestinal epithelial cells to human Crohn’s disease (Begun et al., 2015; Rioux et al., 2007). Such studies highlight the role of intestinal autophagy in suppression of bacteria-induced inflammatory response in the gastrointestinal tract that is the cause of Crohn’s disease (Nguyen et al., 2013). With the vast number of disease conditions associated with dysfunctional autophagic machinery, it is important to understand the physiological and pathological contributions of autophagy to a variety of human diseases.

AUTOPHAGY There are three autophagic pathways that have been described: macroautophagy, microautophagy, and chaperone-mediated autophagy (CMA). Macroautophagy is the primary pathway for the sequestration of large cytoplasmic constituents by double-layered membrane vesicles known as autophagosomes. Microautophagy is characterized by the engulfment of cytoplasmic materials through the invagination of the lysosomal membrane. CMA is a selective degradation process whereby a chaperone (hsc70) recognizes and binds specific cytosolic proteins that contain a pentapeptide consensus motif. This complex is then ushered to the lysosome by way of co-chaperones and the lysosomal-associated membrane protein (LAMP) type 2A (Orenstein and Cuervo, 2010). In the end, all sequestered cargo delivered to the lysosomes or vacuoles is degraded and then appropriated throughout the cell (Wang and Qin, 2013). Both macroautophagy and microautophagy have the capacity to engulf large structures, yet macroautophagy is the only known cellular pathway for removing large organelles such as mitochondria (Mizushima et al., 2008). Macroautophagy (herein referred to as “autophagy”) has been linked to immunity and will be the focus of this review. Autophagy-related genes (ATG) were initially identified in Saccharomyces cerevisiae (baker’s yeast) during the early 1990s and since then, over 30 distinct ATG genes have been discovered in yeast (Xie and Klionsky, 2007). Importantly the autophagy process is highly conserved from yeast to plants and animals. Multiple mammalian autophagy proteins have been found allowing studies into the mechanisms of autophagy related to human diseases (Mizushima, 2007).

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In most cell types autophagy is continuously active at basal levels, yet it can be further induced in response to cellular stress to regulate energy and maintain intracellular stability. Consequently, autophagy functions in a cellular “house-keeping” capacity to maintain organelle and protein integrity. There are many signals for the induction of autophagy including but not limited to critical cellular developmental stages, hypoxia, starvation, endoplasmic reticulum stress, and microbial infection (Glick et al., 2010). Autophagy is strongly induced under starvation conditions. During nutrient deprivation, the target-of-rapamycin (TOR), a serine/threonine protein kinase functioning downstream of growth factor receptor signaling, is repressed (Codogno and Meijer, 2005). TOR inhibition allows dephosphorylation of the normally hyperphosphorylated Atg13 that can then bind to and activate the protein kinase Atg1, initiating autophagy (Kamada et al., 2010). The energy sensor AMP-activated protein kinase (AMPK) has also been demonstrated to induce autophagy by inactivation of TOR and/or through the direct phosphorylation of ULK1, the mammalian ortholog of Atg1 (Egan et al., 2011; Hardie, 2011; Kim et al., 2011). Upon autophagy induction, a crescent membrane termed phagophore forms and sequesters cytoplasmic constituents. Then the phagophore membrane elongates and closes to form the double-membrane autophagosome. At last, the autophagosomes fuse with lysosomes or vacuoles to form autolysosomes. The inner membrane of the autophagosome and the sequestered cellular components are degraded by lysosomal/vacuolar hydrolases (Fig. 15.1) (Levine and Klionsky, 2004). In addition to degradation of cellular components, autophagy can also capture and eliminate bacterial pathogens including Salmonella (Yuk et al., 2012).

SALMONELLA Salmonella are rod-shaped, Gram-negative bacteria belonging to the family Enterobacteriaceae. Infectious strains can invade mammalian cells and promote selfsurvival as they replicate, causing illness. Two species of Salmonella have been identified: Salmonella bongori and Salmonella enterica. S. bongori have been predominately isolated from cold-blooded animals such as reptiles (Brenner et al., 2000). In contrast, S. enterica cause tens of millions of human infections annually worldwide. There are six subspecies of S. enterica: enterica (I), salamae (II), arizonae (IIIa), diarizonae (IIIb), houtenae (IV), and indica (VI) (Agasan et al., 2002). Over 2600 serovars are recognized among these subspecies; the most pathogenic to humans, S. enterica subsp. enterica, account for approximately 60% of the serovars (den Bakker et al., 2011; Fookes et al., 2011). Using the Kauffman–White classification scheme, distinct serovars are divided based on their cell surface antigens; “O” antigen is determined by the oligosaccharide moiety of lipopolysaccharides (LPS) and “H” antigen is determined by flagellar proteins (Brenner et al., 2000). Serotypes of S. enterica subsp. enterica include: Salmonella Choleraesuis, Salmonella Dublin, Salmonella Sendai, Salmonella Enteritidis, Salmonella Typhi, and Salmonella Typhimurium (Coburn et al., 2007). The various serovars present an array of symptoms ranging from acute vomiting, diarrhea, and abdominal pain associated with gastroenteritis to rash and delirium that can accompany potentially life-threatening systemic enteric fever (Jantsch et al., 2011; Malik-Kale et al., 2011). In addition to serotype, symptom manifestation correlates to host vulnerability as well as the amount of bacterial exposure. Salmonella Enteritidis is the most reported serovar globally

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FIGURE 15.1 Schematic of classical autophagy. AMPK and TOR kinases regulate autophagy induction by targeting a serine-threonine kinase complex containing ATG1, ATG13, and ATG17. After induction, the isolation membrane termed phagophore begins to envelop and sequester cytosolic material and forms a double-layered membrane known as an autophagosome. The outer membrane of the autophagosome subsequently fuses with a lysosome. Lysosomal hydrolases degrade the inner membrane and then the cytoplasmic material contained within the autophagosome. AMPK, AMP-activated protein kinase; TOR, target-of-rapamycin.

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and accounts for 85% of Salmonella cases in Europe; Salmonella typhimurium is the second most common serovar (Coburn et al., 2007; Hendriksen et al., 2011). During the year 2000, there were an estimated 21,650,974 reports of typhoid fever resulting in 216,510 deaths. In addition, paratyphoid fever caused 5,412,744 cases of illness globally (Crump et al., 2004). Even with improvements in sanitation, as the global populations of Salmonella expand, reports of disease incidence are likely to continue to increase.

INVASION OF SALMONELLA INTO INTESTINAL EPITHELIUM CELLS S. enterica infection initiates with the ingestion of contaminated food, water, or from close contact with an infected host (Fàbrega and Vila, 2013). Following ingestion, Salmonella that survive gastric acidity colonize in the ileum and cecum of the intestine where they can enter host cells using a variety of virulence factors, most importantly, type III secretion systems 1 and 2 (T3SS1/T3SS2) (Coburn et al., 2007; Jantsch et al., 2011). T3SS1 and T3SS2 are encoded by two chromosomal clusters of pathogen-specific virulence genes known as Salmonella pathogenicity islands (SPI1 and SPI2) that are functionally and temporally distinct (Coburn et al., 2007; Malik-Kale et al., 2011; Ong et al., 2010). Salmonella can penetrate the intestinal epithelium through phagocytic M-cells (Peyer’s patches) and nonphagocytic enterocytes. Once in the intestinal lumen, Salmonella adhere to epithelial surface proteins on host cells. Bacterial adhesion is mediated by Salmonella fimbrial adhesion proteins including: type I fimbriae (FimH), Pef fimbriae, Std fimbriae, and curli fimbriae (Fàbrega and Vila, 2013; Kisiela et al., 2012). Salmonella can enter host cells in a T3SS1-dependent or T3SS1-independent manner, although the former is most efficient for bacteria regarding nonphagocytic cells. In a T3SS1-dependent manner, Salmonella inject multiple virulence proteins (e.g., SipA, SipB, SipC, SopB, SopE, and SopE2) into epithelial cells. Consequently, membrane ruffles are induced on the cells surface membrane creating vacuoles or macropinosomes that may contain Salmonella (Coburn et al., 2007; Haraga and Miller, 2003; Malik-Kale et al., 2011). As a result of these virulent effector proteins, host cytoskeletal dynamics are modified by stimulated Rho GTPases (Cdc42, Rac1, and RhoG) that drive actin nucleation via the Arp2/3 complex. Recently, Salmonella have been demonstrated to induce the transdifferentiation of follicular-associated epithelial cells into M-cells in a SopB required process (Tahoun et al., 2012). This increase in M-cell density enhances the ability of Salmonella to cross the epithelial barrier by transcytosis where macrophages internalize them by phagocytosis (Fig. 15.2). Internalized Salmonella in both macrophages and nonphagocytic enterocytes reside within the Salmonella-containing vacuole (SCV), a membrane-bound structure that becomes modified and maintained by virulent proteins from both T3SS1 and T3SS2. The SCV briefly recruits early-endosomal antigen 1 (EEA1), Rab5, and transferrin receptor (TfR) but replaces them with late-endosomal markers as the SCV matures. These late-endosomal markers include: LAMP1, LAMP2, LAMP3, and the vacuolar proton-pump ATPase (V-ATPase) (Kuhle and Hensel, 2004; Steele-Mortimer, 2008). Interestingly the host cell uses the ATPase acidification to activate hydrolytic enzymes inside the phagosomal lumen, while it is thought that Salmonella uses this change in pH as a mechanism to stimulate intracellular induction of T3SS2 activity (Drecktrah et al., 2007). Although the SCV shares common

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FIGURE 15.2 Depiction of Salmonella invasion into intestinal epithelium cells and Salmonella elimination by autophagy. Salmonella can enter host cells by transcytosis through phagocytic M-cells or by SP1-mediated entry of nonphagocytic intestinal epithelia. Internalized Salmonella in macrophages and epithelium cells reside in SCV. Sp1-mediated SCV damage allows Salmonella to enter into cytosol, where Salmonella are ubiquitinated, captured by autophagosomes, and eliminated. SCV, Salmonella-containing vacuole.

characteristics with the endosome, much remains unclear concerning the mechanisms by which normal phagosomal maturation is manipulated for the sake of bacterial survival and replication within SCVs. There are many immunological pathways employed by host cells for clearance of foreign bacteria and perhaps as many mechanisms evolved by bacteria used for circumvention. This competition begins after infection and continues throughout the bacterium–host cell interaction. Host cells can eliminate Salmonella in SCV by locally accumulating high concentrations of antimicrobial peptides, reactive oxygen intermediate (ROI), and reactive nitrogen intermediate (RNI) (Yuk et al., 2012). However, Salmonella PhoP/PhoQ two-component regulatory systems are activated upon infection, leading to LPS modification and cationic antimicrobial peptides resistance (Sanowar and Le Moual, 2005). Moreover, in response to host-reactive molecule defenses, Salmonella can suppress inducible nitrogen oxide synthase induction and resist oxidants by SPI2-mediated interference of phagocyte NADPH oxidase trafficking; this process also grants evasion of ROI and RNI (Chakravortty and Hensel, 2003; Vazquez-Torres et al., 2000). To survive in the acidic environment of SVC, Salmonella can trigger the acid tolerance response that produces a pH-homeostatic function to maintain the pH of SCV above 5–5.5 within the vesicle (Fàbrega and Vila, 2013; Foster and Hall, 1991). Furthermore, Salmonella can persist in SCV for hours or even days through biogenesis modification and

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SPI2-mediated maintenance of SCV (Birmingham et al., 2006; Brumell et al., 2001; Jantsch et al., 2011). The ability of Salmonella to evade and counter various defenses increases virulence and the host cell susceptibility.

INTESTINAL AUTOPHAGY IN HOST DEFENSE AGAINST SALMONELLA Autophagy-mediated intracellular pathogen elimination, termed xenophagy, is a process in which certain bacteria are targeted to lysosomes for degradation by autophagic machinery (Choy and Roy, 2013; Levine et al., 2011). It has been demonstrated that group A Streptococcus (GAS) is internalized into endosomes once they invade HeLa cells. These GAS-containing endosomes fuse with lysosomes to form autophagolysosomes in which the majority of bacteria is destroyed. This process depends on autophagy genes Atg5 and LC3/ ATG8, Rab5 and Rab7 (Nakagawa et al., 2004; Sakurai et al., 2010; Yamaguchi et al., 2009). Indeed, xenophagy has been shown to target several pathogens in different animal models such as Listeria monocytogenes in Drosophila (Yano et al., 2008), Francisella tularensis and Mycobacterium tuberculosis in murine macrophages, and Salmonella enterica in Caenorhabditis elegans, with varying success regarding restriction of bacterial replication (Birmingham et al., 2006; Jia et al., 2009; Py et al., 2007; Rich et al., 2003). Mammalian intestinal epithelia is particularly important in immune responses due to persistent interfacing with commensal and potentially pathogenic bacteria (Benjamin et al., 2013). Salmonella bacteria are known to initiate infection of mammalian hosts by penetrating the intestinal epithelium of ileum and cecum. After invasion into intestinal epithelial cells, Salmonella usually reside and replicate within membrane-bound SCV. The Salmonella SPI1 TTSS membrane pore-forming activity can lead to SCV damage, which allows Salmonella to enter the cytosol (Birmingham et al., 2006). Cytosolic Salmonella bacteria are ubiquitinated and captured by autophagosomes for degradation (Fig. 15.2). It has been reported that ubiquitinated Salmonella are recognized by specific adaptor proteins, p62/SQSTM1 and NDP52, that interact with the autophagosomal protein LC3/ATG8 (Cemma et al., 2014; Thurston et al., 2009). Depletion of these individual adaptors results in impairment of antibacterial autophagy, suggesting p62 and NDP52 may help recruit membrane to generate autophagosomes around bacteria through their binding to LC3. However a recent study suggests a different model. Fujita et al. proposed that the selectivity of autophagy against Salmonella is not determined by the interaction between adaptor proteins and LC3. Instead, ubiquitinated Salmonella are recognized by three pivotal components of the autophagic machinery including the ATG16L1 complex, the ULK1 complex, and Atg9L1 (Fujita et al., 2013). ATG16L1 and immunity-related GTPase family M protein (IRGM), along with other proteins, form a complex that stimulates LC3/Atg8 lipidation with phosphatidylethanolamine (PE), leading to autophagosome generation (Deretic et al., 2008). ATG16−/− yeast and ATG16L1−/− mice do not conjugate LC3/Atg8 to PE and thus lack effectual autophagy (Deretic et al., 2008; Mizushima et al., 1999). In vivo studies confirm the role of ATG16L1 in elimination of invaded Salmonella in intestinal epithelial cells. It has been reported that conditional knockout mice where ATG16L1 is deleted in intestinal epithelia cells are hypersusceptible to S. typhimurium and have fewer Paneth cells (Conway et al., 2013). Paneth cells, residing within the crypts

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of intestinal epithelium, release antimicrobial α-defensins/cryptdins and lysozymes as a mucosal defense against enteric pathogens (Salzman et al., 2003). ATG16L1 deficiency may decrease the secretion of antimicrobial peptides, which allows Salmonella to penetrate the intestinal epithelium. Besides ATG16L1, S. typhimurium infected mice with an intestinal epithelial cell–specific deletion of Atg5 also displayed increased intracellular bacteria and dissemination to extraintestinal tissues (Benjamin et al., 2013). These in vivo studies indicate the essential role of intestinal autophagy in restriction of intracellular growth of Salmonella, which is also supported by studies in C. elegans. The free-living nematode C. elegans has been established as a host model to study the host–pathogen interactions and has provided insight into autophagy-mediated resistance to S. typhimurium (Labrousse et al., 2000). Atg gene bec-1, involved in autophagosome nucleation, was shown to be important in limiting bacterial replication. bec-1 RNAi-treated C. elegans were found to contain numerous bacteria and few autophagosomes within intestinal epithelial cells compared to controls (Jia et al., 2009). Moreover, inhibition of autophagy bec-1 in intestinal cells but not in other tissues significantly increased the sensitivity of C. elegans to Salmonella infection (Curt et al., 2014). In humans, genomewide association studies have implicated the T300A variant of ATG16L1 in susceptibility to Crohn’s disease (Hampe et al., 2007; Rioux et al., 2007; WTCCC, 2007), a chronic debilitating inflammatory bowel disease involving an aberrant response to intestinal bacteria (Hubbard and Cadwell, 2011; Massey and Parkes, 2007). Notably, expression of Crohn’s disease-associated ATG16L1 coding variant in human epithelial cells reduces the autophagic clearance of S. typhimurium (Kuballa et al., 2008; Messer et al., 2013), suggesting that the association of ATG16L1T300A with increased risk of Crohn’s disease is due to impaired bacterial handling and lowered rates of bacterial capture by autophagy. One important question related to bacterial xenophagy is how autophagy is induced upon bacterial invasion. It has been reported that pathogenic cell invasion is sensed by TLRs in macrophages which leads to autophagy and innate immunity activation (Delgado et al., 2008). Intestinal epithelial invasion by S. typhimurium or Enterococcus faecalis can trigger autophagy downstream of TLRs through the activities of myeloid differentiation response gene 88 (MyD88) and TIR-domain-containing adaptor protein inducing IFN-β (TRIF) (Benjamin et al., 2013) (Fig. 15.3). This signaling mechanism has been shown to induce autophagy through competition between the apoptosis regulator protein Bcl-2 and adaptor proteins MyD88 and TRIF, to regulate the critical autophagy Beclin-1/hVPS34 complex (Benjamin et al., 2013; Shi and Kehrl, 2008). In addition to conventional immunity receptors, other autophagy regulators are also involved in autophagy induction regarding elimination of invaded Salmonella. It has been shown that Salmonella-induced membrane damage in intestinal host cells triggers an amino acid starvation program resulting in TOR inhibition which induces integrated stress responses including autophagy (Tattoli et al., 2012). According to a study in chicken muscle cells, Salmonella infection causes alterations in AMPK phosphorylation and activity, which disrupts the TOR signaling pathway and stimulates autophagy (Arsenault et al., 2013). Salmonella infection may also induce autophagy by using a similar mechanism in intestinal epithelia cells (Fig. 15.3). Intestinal epithelial autophagy provides a critical mechanism of resistance to bacterial infection. However, this process may involve further upstream/downstream relays

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FIGURE 15.3 Diagram of autophagy induction upon Salmonella infection. Autophagy plays an important role in downstream stimulation of innate immune responses from Toll-like receptor signaling induced by Salmonella infection. The enhanced signaling is mediated by adaptor proteins (e.g., MyD88 and TRIF). Salmonella-induced membrane damage in intestinal host cells can trigger an amino acid starvation program resulting in TOR inhibition and autophagy induction. In addition, Salmonella infection results in alterations in AMPK phosphorylation and activity, which stimulates autophagy. AMPK, AMP-activated protein kinase; TOR, target-of-rapamycin; MyD88, myeloid differentiation response gene 88; TRIF, TIR-domain-containing adaptor protein inducing IFN-β.

between multiple tissues in a cell-nonautonomous manner. Recently, neuronal upregulation of AMPK or Atg1 has been reported to induce autophagy in both neuronal and intestinal tissues in Drosophila (Ulgherait et al., 2014). Therefore, it is probable that a cross talk between neural and intestinal tissues is involved in regulation of autophagy in defense against Salmonella and other bacterial infections. Interestingly, C. elegans chemosensory BAG neurons employ TOL-1, the sole TLR in C. elegans, in pathogen avoidance (Brandt and Ringstad, 2015). Furthermore, C. elegans with loss-of-function mutations in the neuropeptide receptor 1 (NPR-1) have displayed increased susceptibility to Salmonella infection. NPR-1 is expressed in multiple neurons including PQR, AQR, and URX. These neurons may regulate C. elegans innate immunity in a neuroendocrine fashion (Styer et al., 2008).

CONCLUDING REMARKS Over the years, the complex relationship between Salmonella and host cell immunity has been vigorously studied. Salmonella have demonstrated an assortment of mechanisms which facilitate their own survival and replication by subverting or exploiting host cell immunological responses. Recently, autophagy has been implicated in a wide range of immunological functions including pathogen degradation, lymphocyte survival and homeostasis,

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innate immune cell stimulation, and antigen processing. Although much has been revealed concerning the role of autophagy in host cell immunity, the extensive mechanisms underlying the ability of autophagy to regulate immunity and degrade pathogens still remain elusive. Further experimentation and advancements, especially in vivo studies, will yield a more accurate representation of Salmonella and autophagic machinery interactions. A clearer understanding of these mechanisms may lead to the development of new approaches which target autophagy to treat infectious diseases.

Acknowledgments We apologize to authors whose work could not be included due to space restrictions. We thank Dr. Diane BaronasLowell for critical reading of the manuscript. The work in the laboratory of the authors is supported by NIH 1R15HD080497-01 (K.J.) and an Ellison Medical Foundation New Aging Scholar Award (K.J.).

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16 Autophagy and LC3-Associated Phagocytosis Mediate the Innate Immune Response Larissa D. Cunha and Jennifer Martinez O U T L I N E Autophagy as an Evolutionarily Conserved Survival Mechanism

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Cross Talk Between Autophagy Machinery and Innate Immunity 305 Role of Autophagy Machinery in Innate Immune Mechanisms of Pathogen Elimination 307 Regulation of Innate Immune Signaling Pathways by the Components of the Autophagy Machinery 308 Effects of Autophagy Machinery on the Cross Talk Between Innate and Adaptive Immunity 310

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Mechanisms of Selective Autophagy 313 Mitophagy 313 LC3-Associated Phagocytosis 314 Conclusions 318 References 318

Abstract

Eukaryotes, spanning the cellular complexity gamut from yeast to plant to mammal, possess a tightly regulated mechanism termed macroautophagy (herein referred to as autophagy) that allows them to maintain a supply of nutrients and energy adequate for their survival. Likely evolved as a homeostatic response to cellular stress and/or nutrient deprivation, autophagy also functions as a means of protein and organelle quality control. Although its evolutionary origins lie in the recycling of intracellular materials and removal of damaged proteins and organelles, autophagy in higher eukaryotes has diversified into defense mechanism, capable of confronting immunological and pathogenic stress. Indeed, genetic and biochemical studies have revealed a critical role for the proteins of the autophagy machinery in immune response and inflammation. Therefore autophagy serves as a primordial response to both endogenous and exogenous distress. M.A. Hayat (ed): Autophagy, Volume 11. DOI: http://dx.doi.org/10.1016/B978-0-12-805420-8.00016-0

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AUTOPHAGY AS AN EVOLUTIONARILY CONSERVED SURVIVAL MECHANISM At its core, autophagy is a prosurvival strategy in response to stress. As self-sustaining entities, cells employ autophagy to resolve a wide variety of danger cues, including environmental damage, chemical fluctuations, metabolic stress, or pathogenic stress. During stress, autophagy allows cells to preserve biosynthetic capacity and ATP levels by supplying substrates for de novo protein synthesis and the tricarboxylic acid cycle. The most characterized and most common experimental model for autophagy induction is nutrient deprivation, and it is from this model that we have gained the majority of our insight into the molecular mechanisms of autophagy (Klionsky et al., 2016). The process of autophagy is largely mediated by the ATG (AuTophaGy) family of proteins, with evolutionary origins in yeast. These ATG proteins coordinate the formation of an isolation membrane (or phagophore), the origins of which are still debated. Compelling evidence suggests that the phagophore forms at the mitochondrial-associated ER membranes, sites of mitochondria, and endoplasmic reticulum (ER) interconnectedness that are critical to lipid metabolism and initiation of the autophagic cascade during starvation (Reggiori and Klionsky, 2013). On a molecular level, autophagy is orchestrated during five key stages: phagophore or vesicle nucleation, vesicle elongation, LC3-II decoration and autophagosome formation, fusion with the lysosome to form the autolysosome, and degradation and processing of sequestered components. During times of nutrient deprivation, autophagy is initiated by the activation of the preinitiation complex, composed of ULK1/2, ATG13, and FIP200. Under optimal growth conditions, mammalian target of rapamycin (mTOR), a critical node in nutrient sensing, inhibits autophagy induction by direct phosphorylation of ATG13 and ULK1 of the preinitiation complex. However, during nutrient withdrawal or low-energy scenarios, AMP-activated protein kinase (AMPK) acts as a dual-function positive regulator of autophagy. AMPK induces autophagy both by differentially phosphorylating ULK1 (thus activating it) and simultaneously inhibiting mTOR via phosphorylation of Raptor (Mao and Klionsky, 2011). The Beclin 1-binding partner, Ambra1, directly connects the activity of this preinitiation complex, considered the most upstream regulator of the autophagic process, to the Class III PI3K complex. Ambra1 binds the core components of the Class III PI3K complex, Beclin 1 and VPS34, and holds them at the cytoskeleton through an interaction with the dynein motor complex. Upon autophagy induction, ULK1 phosphorylates AMBRA1, allowing it and its bound partners to relocalize to the ER and initiate vesicle nucleation. The activity and localization of the Ambra1 complex further supports the role of the ER in autophagosome formation (Fimia et al., 2011). Interestingly, AMBRA1 was shown to act in an mTORC1-sensitive positive-feedback loop to promote K63-linked ubiquitination of ULK1 through recruitment of the E3-ubiquitin ligase TRAF6 (Nazio et al., 2013). The Class III PI3K complex functions in the generation of the lipid, PI(3)P, targeted to autophagosomal membranes. This lipid is essential for the recruitment of downstream ATG proteins and autophagosomal membrane formation. Although the Class III PI3K complex contains the core components Beclin 1, VPS34 (the class III Pi3k responsible for PI(3)P), and VPS15, it can differ in its inclusion of additional proteins. ATG14 and UVRAG are evolutionarily conserved proteins, which interact with Beclin 1 in a mutually exclusive manner, thus identifying two distinct Beclin 1 complexes involved in autophagy. How these two

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complexes differ in their function and role in autophagy remains to be determined. Recent studies indicate that ATG14-containing Class III PI3K complexes require ULK1 activity to localize to the phagophore. However the requirement for ULK1 activity in the translocation of the UVRAG-containing complex is unknown. Furthermore, UVRAG can play an additional downstream role in the maturation of the autophagosomes (Fan et al., 2011). Indeed the deposition of PI3P on the forming autophagosomal membranes is critical for the recruitment of two ubiquitylation-like, protein conjugation systems: the ATG5-12-16L and LC3-PE conjugation pathways. These two pathways mediate the elongation, ultimate closure, and maturation of the autophagosomes. Briefly the ubiquitin-like protein, ATG12, is activated by ATG7 (E1-like ligase) and transferred to ATG10 (E2-like ligase). ATG12 is then conjugated to ATG5, forming the ATG12-5 conjugate. With ATG16L, the ATG12-5 conjugate forms multimeric complexes of ATG5-12-16L, which serves as mechanical stabilization for the forming autophagosomes. The other ubiquitin-like protein, LC3 (or ATG8), is processed by ATG4 to its cytosolic form, LC3-I, exposing a carboxyl terminal Glycine. LC3-I is also activated by ATG7, transferred to ATG3 (a second E2-like ligase), and lipidated with phosphatidylethanolamine (PE) to a membrane-bound form, LC3-II. LC3-II is localized to preautophagosomes and autophagosomes, making this protein a key autophagy marker. This lipidated, membrane-associated form remains on the autophagosome during its formation, its completion, and its fusion with the lysosome, though following fusion of autophagosomes with lysosomes, intraautophagosomal LC3-II is degraded by lysosomal hydrolytic enzymes. It is therefore believed that LC3-II is crucial for the targeting of autophagosomes to lysosomal organelles and ultimately successful autophagy (Levine et al., 2011). The importance of these proteins and the autophagy pathway in general has been exemplified by the embryonic or perinatal lethality of animal models deficient for even a single autophagy gene. This phenomenon highlights the essence of the autophagic process, as a program of self-sustained maintenance of cellular homeostasis in order to preserve viability. However, this requirement for the autophagic machinery during development also reveals that this pathway functions during a myriad of biological processes beyond the realm of nutrient stress (Levine et al., 2011).

CROSS TALK BETWEEN AUTOPHAGY MACHINERY AND INNATE IMMUNITY As an evolutionary conserved mechanism of cellular response to conditions of metabolic stress and homeostasis of the intracellular milieu, it is well accepted that the lysosomal degradation pathway controlled by autophagy has divergent functionally to respond to invading intracellular microorganisms. In unicellular organisms macroautophagy exerts a cell autonomous mechanism of degradation of pathogens—in the amoeba Dictyostelium discoideum, for instance, autophagy confers resistance to lethal infection by Salmonella Typhimurium. Besides targeting pathogens for degradation, the autophagy apparatus functionally divergent in complex metazoans, in which they participate in the regulation of different steps of the immune response. Signaling pathways that control effective immune responses to pathogens often convert to activation of autophagy machinery to ensure elimination of the invading microorganism. Conversely, components of the autophagic machinery are also essential

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FIGURE 16.1 Models of Canonical Autophagy (left) and LC3-Associated Phagocytosis (LAP, right). During starvation or other stress, AMPK is activated and inhibits mTORC1, which inhibits the autophagic process under nutrient rich basal conditions. AMPK also activates the pre-initiation complex, composed of ULK1/2, FIP200, and ATG13. This complex then activates and recruits the Class III PI3K complex, composed of the core components Beclin 1, VPS34, and Atg14 or UVRAG. VPS34 generates PI(3)P which serves as a recruitment signal for the downstream ubiquitin-like conjugations systems, ATG5-12 and LC3-PE conjugation systems. The activity of these complexes results in membrane curvature and closure and lipidation of LC3 (LC3-II). In LAP, receptor engagement during phagocytosis triggers the recruitment of the UVRAG- and Rubicon-containing Class III PI3K complex, resulting in significant PI(3)P deposition on the LAPosome. This PI(3)P is required for the recruitment of downstream ATG5-12 and LC3-PE conjugation systems and stabilizes the NOX2 complex. Rubicon itself also stabilizes the NOX2 complex, promoting optimal ROS production. Both PI(3)P and ROS are required for progression of LAP. Maturation of the LAPosome via fusion to the lysosome also requires the presence of LC3-II.

for efficient pathogen recognition, processing and presentation of antigens, and regulation of pathways for cytokine production. Besides, maturation and homeostasis of lymphocytes are also regulated by autophagy, showing that this process also contributes for an efficient adaptive immune response. Not surprisingly, reciprocity between autophagy and innate immunity—and mutations in important components of the autophagic pathway that affect their balance—has been strongly associated to susceptibility to several autoinflammatory disorders, as well, as in neurodegenerative and age-related diseases (Fig. 16.1).

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Role of Autophagy Machinery in Innate Immune Mechanisms of Pathogen Elimination The autophagy machinery can also be selectively recruited to intracellular and vacuolar viruses and bacteria to serve a specific antimicrobial role. This selective autophagosomal degradation of foreign microbes is termed “xenophagy” and can play an important role in the resistance to infections. Xenophagy was first identified as an effector mechanism of degradation of group A Streptococcus by embryonic stem cells and Mycobacterium by macrophages. Although xenophagy is recognized as a broad mechanism of effector innate immunity against pathogens of different classes—virus, intracellular bacteria, and parasites—the detailed mechanisms of the process are not completely understood. Different pathways have already been identified that lead to formation of autophagosomes-containing bacteria: fusion of mature autophagosome to bacterial vacuole, LC3-associated phagocytosis (LAP), direct recruitment of the autophagy machinery to the phagosome membrane recognition of pathogens that escape the vacuole, “envelopment” of the bacterial-containing vacuole by autophagic membranes, and xenophagic capture of intracellular pathogens that escape into host cell cytosol (Levine, 2005). In the case of Mycobacterium tuberculosis and Mycobacterium bovis bacillus Calmette– Guérin (BCG), autophagosomes are fused to bacterial-containing vacuoles, promoting bacterial clearance. Treatment of macrophages with autophagy inducer rapamycin increases colocalization of LC3 to bacterial vacuole, vacuole acidification, and bacterial degradation, whereas treatment of the cells with Vps34 inhibitor 3-methyladenine favors pathogen survival within the cells. Recognition of pathogens by pattern recognition receptors can also drive directly recruitment of certain components of the autophagy machinery. Upon engulfment, specific moieties of Shigella flexneri peptidoglycan are recognized by NOD2 in the vicinity of the bacterial vacuole. ATG16L1 is recruited to the bacterial vacuole by NOD2, culminating in LC3 lipidation of the membrane and bacterial degradation. In the case of Salmonella enterica Typhimurium the mechanism of bacterial degradation mediated by autophagy is better understood. Cellular disturbance caused by the activity of the bacterial type III secretion system triggers recognition of bacterial-containing vacuole by the lectin galectin-8. Galectin-8 in turn recruits nuclear dot protein 52 (NDP52), an adaptor protein containing an LC3-interacting region (LIR) that recognizes LC3 and mediates engulfment of the bacterial vacuole by the elongating autophagosome (Thurston et al., 2012). Xenophagy of cytosolic pathogens is regulated similarly to those of selective autophagy of endogenous cargo, mediated by adaptor protein containing an LIR, such as p62 (SQSTM1), NDP52, and NBR1. In the case of the adaptor p62, it has already been shown to target bacterial pathogens Salmonella Typhimurium (also described to be targeted by NDP52), S. flexneri, and Listeria monocytogenes that escape their endocytic vacuoles, as well as viruses, to the autophagosomes (Shibutani et al., 2015). The adaptor p62 has also been shown to target to degradation of remnants of bacterial vacuoles, thus eliminating signals that otherwise would lead to cell death and NF-B-dependent cytokine production and cell death. Importantly, in human cells, more than 60 other adaptor proteins that may interact with LC3 and other members of ATG8 orthologs family have been identified, suggesting that other host proteins might be involved in pathogen targeting to autophagy.

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Besides direct pathogen degradation by autophagolysosome formation, the autophagy machinery can mediate restriction of pathogens by regulating different events. Cytosolic proteins are recruited by p62 and processed into antimicrobial peptides in the interior of the autophagosomes, contributing to degradation of M. tuberculosis in the interior of these compartments. In murine macrophages IFN-γ-mediated destruction of Toxoplasma gondii parasitophorous vacuole requires recruitment of IFN-γ-inducible p47 GTPase IIGP1 (Irga6) and p65 guanylate-binding protein (GBP) by different components of the LC3 conjugation machinery, such as ATG7, ATG4, and the ATG5-ATG12-ATG16L1 complex, contributing to infection control in vitro and in vivo. Interestingly, other components as ATG14 and ATG9a are dispensable for LC3 targeting to T. gondii, as well as for Irga6 and GBP recruitment, suggesting that LAP may play an important role in innate immunity against intracellular parasites (Levine et al., 2011). Finally, as the autophagy machinery plays a pivotal role in the host response to pathogens, it is not surprising that different subversion strategies targeting autophagy pathway have already being identified. Pathogens are capable to evade interaction with the autophagy machinery, inhibit activity of components of the autophagy machinery, or else manipulate regulators of autophagosome formation. On the other hand, induction of autophagy is a common subversion strategy, promoting viral intracellular cycle and establishment of bacterial replicative niche, as well as providing a mechanism to regulate host signal transductions pathways. Legionella pneumophila contained within an endosomal bacterial vacuole secretes through a type IV bacterial secretion system a bacterial effector, RavZ, which irreversibly uncouples LC3 from the autophagosome membrane, thus inhibiting further autophagosome elongation. Different virulence factors of viruses have been shown to target Beclin 1 function, thus inhibiting autophagosome initiation and elongation. Beclin 1 activity is blocked by directing interaction with viral virulence factors such as Herpes simplex virus-1 protein ICP34.5 or BCL2-like proteins of Kaposis sarcoma herpes virus, HIV accessory protein Nef and influenza virus matrix protein 2 (Dreux and Chisari, 2010). At the same time, several observations enforce that viruses are capable to exploit autophagy and autophagy machinery to benefit different aspects of viral replication cycle, such as generation of free fatty acids, initiation of translation of genetic material, trafficking, formation of replication compartment, and egression of viral particles. Moreover, other intracellular pathogens hijack the autophagy machinery. The intracellular bacteria Coxiella burnetii actively recruits preformed autophagosomes to their bacterial-containing vacuoles, a strategy that is believed to provide membrane for the expanding vacuole and nutrients necessary for bacterial replication (Moffatt et al., 2015).

Regulation of Innate Immune Signaling Pathways by the Components of the Autophagy Machinery Production and secretion of inflammatory cytokines, generation of antimicrobial reactive species, and induction of cell death are effector mechanisms of innate in response to infection or danger signals. However, those constitute tightly regulated processes as the detrimental effects caused by hyperinflammation are in the core of immunopathologies. Autophagy has also been shown to regulate three major pathways of cytokine production by macrophages in response to infection: inflammatory cytokine transcription mediated by

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NF-κB, type I interferon (IFN) production dependent on nucleic acid receptors, inflammasome activation, and release of inflammatory IL-1β. Activation of the transcription factor NF-κB constitutes a major hub for innate immune production of cytokines and induction of genes of the antimicrobial response. Both transmembrane receptors of the TLR family (with the exception of TLR9) and cytosolic Nod-like receptors (NLRs, specifically NOD1 and NOD2) converge to phosphorylation and activation of NF-κB. Prolonged synthesis of NF-κB targets such as IL-1 and tumor necrosis factor (TNF) is potentially damaged to the host. Although direct evidence of a role of autophagy to avoid an exacerbated inflammation during activation of innate immune response, some clues from host–pathogen interaction points toward that direction. The virulence factor of M45 of cytomegalovirus induces irreversible degradation of NF-κB essential modulator (NEMO), the regulatory subunit of the IKK complex responsible for NF-κB activation. M45 interacts with NEMO, redirecting it for autophagy and lysosomal degradation, thus dampening secretion of proinflammatory cytokine by infected cells (Fliss et al., 2012). Transcription regulation mediated by type I IFN is a pivotal defense mechanism against virus, although low levels of type I IFN production has also been associated to efficient antibacterial immunity. Different components of the autophagy machinery have been shown to regulate diverse aspects of the pathways for induction of type I IFN. Nucleic acid ligands of TLR7 and TLR9 (ssRNA and CpG oligodeoxynucleotides, respectively), as well as TLR8 activation by imidazoquinolines, trigger production of type I IFN by different subsets of dendritic cells (DCs). A role of autophagy in intracellular trafficking to induce TLR activation has been recognized. TLR7-dependent production of type I IFN in response to viral infection is impaired in Atg5-deficient plasmacytoid DCs (pDCs). Canonical macroautophagy addresses intermediates of viral replication to the appropriate endosomes containing TLR7 (Lee et al., 2007). Recognition of cytosolic RNA or DNA by intracellular receptors RIG-I and cyclic GMPAMP synthase (cGAS), respectively, mediate production of type I IFN by activation of the transcription factor interferon regulatory factor 3 (IRF3). Macroautophagy inhibits both RIG-I and its adaptor mitochondrial antiviral signaling (MAVS), the signal transducer downstream of RNA recognition. The conjugate ATG12-ATG5, dependent on E1 activity of ATG7, directly interacts with these molecules, targeting them for degradation. Direct binding of Beclin 1 is also suggested to negatively regulate cGAS activity by inhibiting production of secondary messenger cyclic GMP-AMP (cGAMP), therefore tuning down type I IFN production (Liang et al., 2014). In addition, ATG9a regulates traffic of the complex between STING, the transducer adaptor of cGAS, and the kinase TBK1, resulting in phosphorylation of IRF3. In this case, ATG9a does not require other components of the macroautophagy, such as ATG7. Finally, phosphorylation of cGAS activity drives dissociation of ULK1 from the repressor AMPK, which in turn phosphorylates and inactivates STING. This negative feedback regulatory switch prevents sustained activation of STING, thus avoiding persistent transcription of innate immune genes (Konno et al., 2013). Such strict regulatory system is required as deregulated type I IFN transcriptional activity is associated with autoimmune diseases, constituting a hallmark of patients with systemic lupus erythematosus (SLE). Of note, persistent activation of cGAS and STING has been shown to cause lethal inflammatory system in response to self-DNA in mice, therefore indicating that loss of regulation of these pathways may play a role in autoimmune diseases in humans.

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The inflammasome is a molecular platform triggered upon recognition of molecular signatures derived from pathogens or recognition of autologous danger signals by intracellular NLRs and nucleic acid receptors AIM2-like. Inflammasome formation culminates in activation of cysteine protease caspase-1, which regulates maturation and/or secretion of potent inflammatory cytokines IL-1β, IL-18, and IL-1α and an inflammatory form of cell death– denominated pyroptosis. Although playing a major role in the innate immune response and control of infection by intracellular pathogens, deregulated activation of inflammasome is extremely deleterious and is associated to inflammatory syndromes and metabolic diseases such as cold autoinflammatory syndrome, Alzheimer’s, gout, type 2 diabetes, and atherosclerosis. Autophagy is an important component of the inflammasome regulation network, possibly interfering with different steps of the pathway that might lead to harmful effects of uncontrolled inflammasome activation. Early observations revealed that chimeras with Atg16l1 deficiency in fetal liver hematopoietic precursors render mice susceptible to IL-1βand IL-18-mediated intestine inflammation in an experimental model of colitis induced by dextran sulfate sodium. Assembled AIM2 and NLRP3-dependent inflammasome platforms are ubiquitinated and targeted to autophagosome by p62, culminating in their degradation and limiting cytokine secretion. In that sense, direct targeting of NLRs to autophagy may play a broader role in inflammasome regulation, as recent studies demonstrate that a subset of tripartite motif proteins direct NLRP3, NLRP1, and caspase-1 itself to degradation. In the case of NLRP3 sensor a role for elimination of damaged mitochondria has been established in macrophages, as depletion of LC3B or Beclin 1 results in enhanced caspase-1 activation, possibly by uncontrolled release of NLRP3-activating signals. Moreover, genetic deletion of NLR receptor NOD2 also causes accumulation of damaged mitochondria and deregulated activation of NLRP3 inflammasome in macrophages. In response to influenza A infection, NOD2 induces ULK1-dependent mitophagy, resulting in inhibition of NLRP3 activation. Defects in this regulatory mechanism trigger IL-18-mediated immunopathology in the lungs of mice during experimental infection with influenza. Furthermore, exacerbated IL-18 secretion in mice lacking Atg7 or Atg5 in myeloid cells leads to lethal lung inflammation, supporting an essential role of autophagy to avoid deleterious effect of deregulated secretion of inflammasome-dependent cytokines. Autophagy limitation of inflammasome activation is further increased by sequestration and degradation of pro-IL-1β in autophagosomes (Guo et al., 2015).

Effects of Autophagy Machinery on the Cross Talk Between Innate and Adaptive Immunity During infection, the impact of autophagy in modulation of the innate immune response can also indirectly exert its effects in the adaptive immunity. The cytokine milieu created by antigen-presenting cells (APCs, such as macrophages and DCs) will impact the activation and differentiation of lymphocytes. Type I IFN, for instance, is critical for activation and clonal expansion of CD8+ cytotoxic T lymphocytes and to modulate its activity upon target cells, constituting an essential mechanism in the antiviral response. As mentioned before, autophagy impacts type I IFN production by DCs in response to TLR activation. It is also well documented that autophagy can directly determine successful activation of adaptive responses to infection. Whenever professional phagocytes rely on PRR to sense and respond to pathogens and danger signals, adaptive immunity depends on recognition

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on presentation of processed antigens on major histocompatibility complex (MHC) molecules by APCs and target cells. Selective viral autophagy is required for antigen presentation, and inhibition of autophagolysosome maturation leads to antigen accumulation in immature autophagosomes. In agreement, although DCs conditionally deficient for Atg5 have normal development, migration, and phagocytic activity, they present defects in phagosome maturation. Consequently, processing and presentation of antigens is impaired in these cells, impairing CD4+ T-cell priming and rendering mice susceptible to viral infection. On the other hand, induction of autophagy stimulates loading of antigens onto MHC class II and increases antigen presentation, which most likely can improve the efficacy of vaccines, as already shown for BCG vaccine. In addition a role for macroautophagy has been identified in cross-presentation of antigen onto MHC class I. Macroautophagy promotes efficient antigen loading on MHC class II, overcoming inefficient TAP-dependent antigen processing during viral infections due to proteasome degradation and blockage of peptides traffic through the ER. Autophagy is an essential component of the development, homeostasis, and effector functions of T lymphocytes. However, autophagy also determines early elimination of autoreactive T lymphocytes during negative selection in the thymus, by modulating MHC class II antigen presentation in thymic epithelial cells (TECs). Lack of self-tolerance in athymic mice engrafted with Atg5-deficient thymus lobe causes an autoimmune colitis and systemic inflammation. Macroautophagy and lysosomal processing of cytoplasmic content for loading on MHC class II is perhaps involved in antigen presentation by TECs and thymic negative selection, but such putative mechanism requires further exploration (Shibutani et al., 2015).

Role of Autophagy-Related Genes in Autoimmunity Inappropriate innate immune responses against the self are in the core of the development autoimmune disorders. Persistent activation of innate immunity pathways may occur for different causes, from disruption of cell homeostasis and generation of danger signals misinterpreted by the innate immune cells, passing by mutations that render PRR constitutively active, to disruption in the regulatory circuits of the innate immune response. Once autophagy is essential for development of appropriate immune responses and regulation of inflammation, it is also becoming clear that mutations that impair normal function of the diverse autophagy pathways are relevant in the development of autoimmune syndromes. Genomewide association studies (GWAS) have revealed association between autoimmune diseases in humans and mutations, or single nucleotide polymorphisms, in genes controlling the autophagic pathway. Of note, recent experimental evidence from mouse models has supported the importance of the autophagy pathways and its components for appropriate immune responses and pivotal in the control of autoimmune diseases. Several autoimmune diseases have been associated to autophagy regulation, cystic fibrosis, and multiple sclerosis. Of note, robust evidence from GWAS and experimental models support an important role of autophagy to susceptibility to Crohn’s disease and lupus. Crohn’s Disease Chronic inflammatory bowel diseases (IBD) include intestinal disorders with etiology poorly understood, including Crohn’s disease and ulcerative colitis. However, alterations

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in the microbiome (dysbiosis) are now emerging as an important component involved in susceptibility to IBD. In the last years it became evident that the gut microbiota and the immune system have a tight reciprocity relationship: whereas the commensal bacteria regulate the development and function of the immune system, a competent immune system also determines the composition of the microbiota. Crohn’s disease was the first disease to be associated to mutations in pivotal components of the autophagy machinery. Mutations leading to variants of NOD2 are the strongest risk contributing to Crohn’s disease susceptibility (the three major ones being a frameshift mutant and two missense mutants), as confirmed by GWAS in different demographic populations, thus suggesting a link between response to microbes and autoimmunity. A role of NOD2 in regulation of microbiota and predisposition to gut inflammation and colitis has already been identified in mouse models. Furthermore, GWAS also indicated multiple high-ranking associations between Crohn’s disease and genetic variants in ATG16L1 (Wlodarska et al., 2015). As discussed above, NOD2 induces ATG16L-dependent autophagy in bacteria-infected macrophages. Importantly, the most common NOD2 mutant associated with Crohn’s disease (L1007fsinsC) and homozygosis of the risk allele ATG16L1*300A also impair autophagy in response to bacterial infection or fragments of bacterial wall (muramyl dipeptide) in macrophages. Those findings further support the association between failure to respond to bacteria and susceptibility to Crohn’s disease (Travassos et al., 2010). Defects in ATG16L1 in hematopoietic progenitors cause higher circulation of inflammatory cytokines and development of a microbiome-driven chronic intestinal inflammatory disorder in mice (Saitoh et al., 2008). This suggests a potentially interesting link between NOD2 and ATG16L1 in regulation of autophagy and autoinflammation, as NOD2 regulates autophagy-dependent inflammatory responses during infection (Lupfer et al., 2013). Importantly, in vitro evidence supports that NOD2 and ATG16L1 regulate autophagy-dependent antigen presentation on MHC class II and to activation of CD4+ T cells in DCs. These findings are extended to human DCs, since cells from individuals with Crohn’s disease risk variants ATG16L1*300A or NOD2 L1007fsinsC are also defective in autophagy and antigen presentation. For the IRGM risk allele, a deletion in the gene promoter region has been associated to Crohn’s disease. Of note, experimental data supports that both human IRGM and the murine ortholog is important for autophagy in response to bacteria in macrophages, contributing to bacillus elimination. Once autophagy deficiency and impairment of host immune responses are fundamental outcomes of these important genes of Crohn’s disease, further studies will perhaps clarify any mechanistic link between them and the innate responses to the microbiome. Systemic Lupus Erythematosus SLE is a complex, multifactorial autoimmune disease with unknown causes but influenced by genetic predisposition. Increased serum levels of type I IFN and IFN-induced gene expression are frequently observed in patients with SLE, possibly contributing to the pathogenesis of the disease as it correlates with disease severity (Crow, 2014). Defective engulfment of dying cells has also been implicated in the pathogenesis of SLE. In that sense, mice with impaired clearance of dying cells present enhanced inflammation, with increased cross-presentation and lymphocyte hyperactivity and develop symptoms of a lupus-like syndrome during aging. Atg5 was discovered among the risk loci to SLE, with different associated polymorphisms identified, supporting a role of autophagy in the disease (Raychaudhuri et al., 2009).

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MECHANISMS OF SELECTIVE AUTOPHAGY Mitophagy Canonical autophagy is a nonselective process, wherein the bulk catabolism of cellular components supplies nutrient-deprived cells with the necessary metabolic tools for survival. However the autophagic machinery can be targeted to specific substrates in need of degradation, as their persistence would be detrimental to the cell. One such target of selective autophagy is the mitochondria. Although mitochondria are critical for metabolic functions of fatty acid oxidation, the Krebs cycle, and oxidative phosphorylation, damaged or aged mitochondria must be removed from cells in an efficient manner, as they can also potentially harm cells. Mitochondria are a source of reactive oxygen species (ROS), in particular superoxide anion (i OH), hydrogen peroxide (H2O2), and hydroxyl radical (O 2i−), toxic by-products of oxidative phosphorylation. Furthermore, damaged mitochondria leak high amounts of Ca2+ and cytochrome c to the cytosol and thereby trigger apoptosis (Ashrafi and Schwarz, 2013). Thus, proper clearance of dysfunctional mitochondria is imperative to cellular survival. While mitochondria have evolved their own intrinsic proteolytic systems to degrade unfolded membrane proteins, recent studies have described the removal of damaged mitochondria via mitophagy, in which the autophagy machinery is recruited to damaged mitochondria to deliver those mitochondrial components to the lysosome for degradation. Despite the overlap in protein machinery, mitophagy is not regulated by nutrient levels and is active under steady-state conditions. Prior to its targeting by autophagy machinery, mitochondria are apportioned into “bite-size” pieces via mitochondrial fission, to facilitate ease of encapsulation and to separate mitochondria for removal from healthy mitochondria within the network (Ashrafi and Schwarz, 2013). Autophagy and mitophagy both share extensive similarities in terms of their pathways, therefore how are damaged mitochondria targeted for clearance by mitophagy, in the absence of activating canonical autophagy in the process? Whereas multiple mitophagy-specific genes have been identified in yeast, higher eukaryotes do not often express these genes. Rather, mammalian cells express a variety of mitophagy receptors, such as NIX1, BNIP3, and FUNDC1, which contain LIR consensus sequences required for LC3 family member binding and mitophagy signaling. NIX was originally shown to be the key mediator of mitophagy in red blood cells where its expression is induced during their maturation to drive mitochondrial clearance. In addition, the presence of cardiolipin on the outer mitochondrial membrane of damaged mitochondria has also been reported to act as a so-called “eat me” signal that binds LC3 to promote engulfment by the autophagosomes (Youle and Narendra, 2011). The most well-characterized pathway for ubiquitin-mediated mitochondria clearance is PINK1-Parkin-mediated mitophagy. The loss of mitochondrial membrane potential (achieved experimentally with the uncoupler carbonyl cyanide m-chlorophenylhydrazone, CCCP) (Narendra et al., 2008) or the accumulation of misfolded proteins triggers the stabilization of PINK1 on the outer mitochondrial membrane. PINK1, a serine/threonine kinase, then phosphorylates ubiquitin on Parkin at Ser65, activating Parkin ubiquitin ligase activity, as well as recruits Parkin from the cytosol. A novel and fundamental role of PINK1 in mitophagy was recently identified, wherein PINK1 generates phopshoubiquitin, considered an essential mitophagic signature, on damaged mitochondria. Parkin amplifies this signal

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by generating more ubiquitin chains on the mitochondria, which are subsequently phosphorylated by PINK1. What links ubiquitin chains on damaged mitochondria to the autophagy machinery are the autophagy receptors, such as NDP52, NBR1, p62, and optineurin (OPTN)? Recent work has characterized the relative roles of individual autophagy receptors in mitophagy. Although p62 and NBR1 are dispensable for Parkin-mediated mitophagy, phospho-ubiquitin binds the primary mitophagy receptors OPTN and NDP52, which then recruit ULK1, DFCP1, WIPI1, and LC3 to mediate mitophagy (Lazarou et al., 2015). Functionally, mitophagy serves multiple roles. In addition to its roles in quality control and cell survival, mitophagy has been shown to be required for adjustment of mitochondrion numbers to accommodate changing metabolic requirements and during specialized developmental stages in mammalian cells, such as during red blood cell differentiation or destruction of sperm-derived mitochondria following fertilization of the oocyte (Ashrafi and Schwarz, 2013). Recent studies have also identified that a failure in clearance of damaged mitochondria leads to increased transformative potential (Ichim et al., 2015). Similarly, accumulation of dysfunctional mitochondria in the brains of patients with Parkinson’s disease (PD) implied a link between mitochondrial quality control and disease pathogenesis. Indeed, the genes encoding PINK1 and Parkin were found to be mutated in certain forms of autosomal recessive of PD (Youle and Narendra, 2011). The innate immune response can also be mediated by mitophagy. Production of mature interleukin (IL)-1β by the NLRP3 (NLR family, pyrin domain-containing 3) inflammasome can be activated by ROS signaling, the source of which is theorized to be mitochondria (Zhou et al., 2011). Multiple studies have demonstrated that defective mitochondria resulted in increased ROS and elevated inflammasome activation. Increased inflammasomes’ activity due to mitochondria-derived ROS has also been observed in monocytes from patients with TNF-receptor-associated periodic syndrome patient monocytes, periodic fever disorder, and IBD. In addition, defective mitophagy can also result in the release of mitochondrial DNA (mtDNA), resulting in the activation of multiple nucleic acid sensors, such as TLR9 and NLRP3, though other reports indicate that classical NLRP3 stimuli induce mitochondrial apoptosis to release oxidized mtDNA upstream of NLRP3 activation (Lazarou, 2015). The mitochondria itself is home to the MAVS protein, an RIG-I like receptor adaptor molecule that interacts with RIG-I and/or MDA5 to for the production of proinflammatory cytokines and type I IFNs. Interestingly the antiviral response to vesicular stomatitis virus infection is hyperstimulated in the presence of defective mitophagy, due to an accumulation of dysfunctional mitochondria, increased mitochondrial ROS, and increased levels of MAVS; however, other studies have demonstrated that healthy mitochondria are required to promote MAVS activity. Other viruses, such as hepatitis B and C viruses (HBV and HCV), exploit mitophagy to promote cell survival and prolonged viral replication. The presentation of mitochondrial antigens by MHC class I molecules is also affected by mitophagy, although further studies are required. Taken together, the relationship between the mitochondrion and the innate immune response is one riddled with complexity and reciprocity (Lazarou, 2015).

LC3-Associated Phagocytosis From an evolutionary perspective, the two conserved systems of phagocytosis and autophagy represent two modes of nutrient acquisition, during abundance and scarcity,

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FIGURE 16.2 Pathologies associated with components of the autophagy and LAP pathways.

respectively. These pathways can converge into a newly described process termed LAP and occurs during the engulfment of pathogens or dead cells (Martinez et al., 2013). Therefore LAP allows us to reimagine the impact of the autophagy machinery on innate host defense mechanisms. Engulfment of extracellular particles, such as certain pathogens, immune complexes (ICs), or dead cells, engages extracellular receptors during phagocytosis, including TLR1/2, TLR2/6, TLR4, FcR, and TIM4 (Martinez et al., 2011, 2015; Henault et al., 2012). This receptor signaling during uptake triggers the recruitment of some, but not all, members of the autophagy machinery to the cargo-containing phagosome. The result is the processing and translocation of lipidated LC3-II to the phagosome, or LAPosome. LAP facilitates the rapid processing of the cargo via fusion with the lysosomal pathway, which can play crucial roles in both the degradation of engulfed pathogens as well as shape the pursuant immune response (Martinez et al., 2011, 2015; Henault et al., 2012). Despite utilizing overlapping components, there are several differences between LAP and canonical autophagy (Fig. 16.2). Although the LC3-decorated autophagosome is a double-membrane structure, EM analysis revealed that the LAPosome is comprised of a single membrane (Martinez et al., 2011). Another important distinction is the rapidity in which LAP occurs. Although autophagosomes can take hours to form, LC3-II can be detected on LAPosomes in as few as 10 min after phagocytosis (Martinez et al., 2011). Although a majority of the core autophagy components are required for LAP, there exist some critical molecular distinctions that distinguish the two processes. As described above, mTOR inhibits the preinitiation complex, and hence autophagy. Furthermore, canonical autophagy requires the ULK1-dependent release of Ambra1, a Beclin 1-interacting protein, from

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the dynein motor complex, and the function of WIPI2. In contrast, LAP occurs independently of the preinitiation complex, Ambra1, and WIPI2 (Martinez et al., 2011, 2015; Henault et al., 2012). Similar to autophagy, LAP requires the activity of the Class III PI3K complex, which contains the core components Beclin 1, VPS34, and VPS15. However, LAP only utilizes the UVRAG-containing Class III PI3K complex, whereas ATG14 is dispensable (Martinez et al., 2015). Recently, a novel component of the LAP pathway was described. Rubicon (RUN domain protein as Beclin 1 interacting and cysteine-rich containing) is a protein that associates constitutively with the UVRAG-containing Class III PI3K complex during LAP, yet is not required for canonical autophagy. During canonical autophagy, Rubicon is a negative regulator, via its inhibition of VPS34 or by blocking GTPase Rab7 activation. During LAP, in contrast, Rubicon uniquely associates with the LAPosome, and Rubicon-deficient cells are completely defective in LAP (Martinez et al., 2015). Rubicon seems to have dual functions in promoting LAP. Studies suggest that Rubicon promotes or stabilizes the association of the active Class III PI3K complex with the LAPosome, thereby localizing VPS34-mediated PI(3)P at the LAPosome for downstream recruitment of the ubiquitin-like conjugation systems, the ATG5–12 and LC3-PE conjugation systems (Martinez et al., 2015). Additionally, Rubicon, and the optimal production of PI(3)P resulting from Rubicon, stabilizes NOX2, the major NADPH oxidase in phagocytes, by interacting with its p22phox subunit via its serine-rich domain (aa 567–625). Notably, NOX2 also interacts with Beclin 1 via the CCD domain (aa 515–550) and VPS34 via the RUN domain (aa 49–180). Finally the p40phox subunit of NOX2 requires PI(3)P binding for its activity and stabilization, and cells deficient for Beclin 1, VPS34, or Rubicon, and subsequently PI(3)P production upon engagement of LAP, are also defective in p40phox localization and ROS production (Martinez et al., 2015). Collectively, Rubicon promotes the association of the active Class III PI3K complex with the LAPosome and the production of PI(3)P. Rubicon and PI(3)P stabilize the active NOX2 complex to promote optimal ROS production, which is also required for successful LAP (Martinez et al., 2015). Thus, LAP and canonical autophagy are molecularly distinct processes. Recent evidence strongly suggests that LAP is a regulator of inflammation under physiologically relevant conditions. LAP can have a significant effect on the immune response to engulfed material such as intraphagosomal yeast or Aspergillus fumigatus (Martinez et al., 2015), as well as its degradation. LAP-deficient animals fail to efficiently clear intranasally administered A. fumigatus and release increased levels of proinflammatory cytokines both locally (lung) and systemically (serum) (Martinez et al., 2015). Although the list of pathogens found in the host cell within a single-membrane compartment decorated with LC3 is growing, including pathogens such as M. tuberculosis, Yersinia tuberculosis, and pathogenic Escherichia coli, how extensively noncanonical pathways of selective autophagy contribute to innate responses to vacuole-isolated intracellular pathogens remain to be better explored (Levine et al., 2011). LAP has also been suggested as an important mechanism for antigen presentation, as phagocytosis of exogenous cargo mediated by TLR activation and subsequent lysosome maturation leads to peptide generation and loading on MHC class II in DCs. In those instances, engagement of LAP may also retard lysosome fusion step pathway, favoring prolonged the antigen presentation on MHC class II by DCs and resulting in sustained CD4+ activation in vitro. A role of LAP in cross-presentation is also supported by studies showing

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that autophagy machinery contributes to MHC class I loading of antigens derived from engulfed pathogens in DCs. Potentially, LAP could also be involved in cross-priming by DCs that phagocytose infected apoptotic cells (Nair-Gupta and Blander, 2013). The generation of specific signaling compartments can also be mediated by LAP. DNA-ICs also trigger TLR9-dependent type IFN production in pDCs. In pDCs, engulfment of ICs, complexes of self-antigen (such as DNA), and autoantibodies induces LAP via engagement of the FcγR. DNA-IC-containing phagosomes from LAP-deficient pDC failure to acquire a late-endolysosomal phenotype, which results in a failure to establish the specialized IRF7-signaling compartment. This acidified compartment is required for TLR9mediated activation of IRF7 and production of the type I IFN, IFN-α. Collectively, these data suggest that LAP could affect the immune response elicited by autoantigens and play a critical role in autoimmunity (Henault et al., 2012). Phagocytes must continuously patrol the body to identify and efficiently clear the billions of dead cells that occur normally during development, stress, infection, or homeostasis. This process, termed efferocytosis, is critical for the prevention of aberrant inflammation and autoimmunity, and persistence of cellular corpses is characteristic of many human autoimmune diseases, such as SLE. The most notable characteristic of the efferocytosis of apoptotic cells, the most common type of dying cell physiologically, is its “immunologically silent” response. Phagocytes that have undergone efferocytosis secrete antiinflammatory cytokines, such as TGFβ and IL-10, while actively suppressing proinflammatory cytokines, such as TNF, IL-1, and IL-12 (Han and Ravichandran, 2011). The mechanisms by which phagocytes mediate this immunologically tolerant response are an area of great interest. Recently, LAP was described as a pathway critical for the clearance of dying cells (apoptotic, necrotic, and necroptotic cells) via engagement of the phosphatidylserine receptor, TIM4. Not only do LAP-deficient macrophages exhibit a failure in phagosomal acidification and subsequent corpse degradation, they also produce dramatically increased levels of IL-1β and IL-6 and significantly less antiinflammatory cytokines, such as IL-10, upon such engulfment. Together, this suggests that the fundamental role of LAP is to shape the appropriate immune response, and its absence can result in unwanted inflammation and defective pathogen control. Accumulating evidence suggests that LAP may be involved in SLE manifestation. As mentioned before, LAP is necessary for appropriate activation of TLR9 signaling upon endocytosis of dsDNA-immune complex, leading to production of type I IFN by DCs (Henault et al., 2012). Importantly, deregulation in TLR9 response to immune complexes is associated to SLE. LAP-deficient macrophages also fail to degraded engulfed dead cells, which accumulate as corpses within the cytosol, much similarly to the “LE” cells described in SLE pathogenesis. Also, whereas it is well established that engulfment of apoptotic cells reduces the expression of inflammatory genes and stimulates secretion of antiinflammatory IL-10, LAP-deficient cell fail to do so. Finally, further evidence is provided by descriptions of development of lupus symptoms in patients with chronic granulomatous disease, which is caused by mutations in NOX2. NOX2 activity and generation of reactive species within the phagosome upon engulfment is one of the requirements for LAP, reinforcing a possible link between LAP and SLE (Martinez et al., 2015). Whether LAP is associated with lupus in mice remains to be further explored.

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LAP can also be triggered in specialized phagocytes, such as the retinal pigment epithelium (RPE). RPE cells phagocytose and digest shed photoreceptor outer segments (POS) daily, a process crucial for supplying nutrients and O2 to the retina and the metabolism of vitamin A for the visual cycle, a series of biochemical reactions that ultimately result in the production of the chromophore 11-cis retinal (RAL) necessary for the phototransduction signaling cascade. LAP is required in the RPE cells for the proper processing of POS and promotion of the visual cycle, and animals with LAP-deficient RPE cells displayed defective POS degradation, diminished production of 11-cis retinal, and decreased visual function with age. Thus, LAP functions to support the visual cycle through the efficient processing of POS by the RPE (Kim et al., 2013).

CONCLUSIONS Over billions of years of evolution, the innate immune system has hijacked the cell survival pathway of autophagy to combat invading pathogens, mediate the appropriate immune response, and alleviate unwanted inflammation. Moreover the autophagy machinery can be recruited in a specific manner to damaged cellular components (mitophagy) or during phagocytosis of particles that engage extracellular receptors (LAP). Despite similar autophagic machinery, the molecular characteristics of these pathways can differ, further differentiating these processes. How these pathways evolved away from each other remains to be determined, as does how these processes regulate the innate immune response.

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II. ROLE IN DISEASE


Abbreviations and Glossary

1AP inhibitor of apoptosis protein 3-MA 3-methyladenine is an autophagy inhibitor 3-methyladenine an autophagy inhibitor 5-Fu 5 fluorouracil AAD amino acid deprivation AAP proteins that mediate selective autophagy Acb acyl–CoA binding protein ACF aberrant crypt foci Adaptive autophagy supply of amino acids for cell survival by autophagy under poor environmental conditions Aggrephagy degradation of ubiquitinated protein aggregates Aggresomes inclusion bodies where misfolded proteins are confined and degraded by autophagy AIF apoptosis-inducing factor AIM Atg8-family interacting motif AKA Aurora kinase A Akt/PKB protein kinase B regulates autophagy AKT1 RAC-α serine/threonine protein kinase ALFY autophagy-linked FYVE protein ALIS aggresome-like induced structures ALP autophagy–lysosome pathway ALR autophagic lysosome reformation ALS amyotrophic lateral sclerosis Ambral activating molecule in Beclin-1-regulated autophagy AMBRA-1 activating molecule in Beclin-1-regulated autophagy protein 1 AMP adenosine monophosphate AMPA alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid AMPAR AMPA receptor Amphisome intermediate compartment formed by fusing an autophagosome with an endosome AMPK adenosine monophosphate–activated protein kinase AP-1 adaptor protein complex 1 Apaf-1 apoptotic protease activating factor-1 APC antigen-presenting cell Apel aminopeptidase 1 precursor API aminopeptidase I aPKC atypical protein kinase C APMA autophagic macrophage activation Apoptosis programmed cell death type 1 occurs during the normal development of multicellular organisms APP amyloid precursor protein ARD1 arrest-defective protein 1 ARE antioxidant-responsive element ARF6 ADP-ribosylation factor 6

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ARHI aplasia Ras homolog member 1 ASC adaptor protein apoptosis–associated speck-like protein containing a CARD ASK1 apoptosis signal regulating kinase 1 AT1 Atg8-interacting protein ATF-2 activating transcription factor 2 ATF5 activating transcription factor 5 ATF6 activating transcription factor 6 ATG autophagy-related gene Atg autophagy-related protein Atg1 serine/threonine protein 1 kinase Atg10 ubiquitin-conjugating enzyme analog; links Atg12 to an internal Lys residue in Atg5 Atg101 Atg13-binding protein; interacts with ULK1 and Atg13 Atg11 fungal scaffold protein Atg12 ubiquitin-like protein; protein is conjugated to Atg5 that functions in the activation of Atg3 Atg13 component of the Atg1 complex; modulates ULK complex activity Atg14 component of the class III PtdIns 3-kinase complex Atg14L protein directs P13K complex to the omegasome (Barkor) Atg15 vacuolar protein Atg16 component of the Atg12-Atg5-Atg16 Atg16L T300A a common threonine to alanine coding variant at position 300 in Atg16L ATG16L1 gene responsible for making autophagy-related 16-like 1 protein Atg17 yeast protein Atg18 protein that binds to PtdIns Atg19 receptor for the Cvt pathway Atg2 protein that functions along with Atg18 Atg20 PtdIns P-binding protein Atg21 PtdIns P-binding protein Atg22 vacuolar amino acid permease Atg23 yeast protein Atg24 PtdIns-binding protein Atg25 coiled-coil protein Atg26 sterol glucosyltransferase Atg27 integral membrane protein Atg28 coiled-coil protein Atg29 protein in fungi Atg2A and Atg2B proteins required for closure of isolation membranes to form autophagosomes Atg3 enzyme conjugates LC3 to phosphatidylethanolamine Atg30 protein required for recognizing peroxisomes Atg31 protein in fungi Atg32 mitochondrial outer membrane protein Atg33 mitochondrial outer membrane protein Atg4 cysteine protease; cleaves carboxy-terminal Gly residues from LC3 homologs and is also required to recycle LC3 from the autophagosome outer membrane Atg5 protein containing ubiquitin folds; protein is conjugated to Atg12 Atg6 component of the class III PtdIns 3-kinase complex Atg7 ubiquitin-activating enzyme homolog; enzyme activates Atg12 and LC3 homologs Atg8 ubiquitin-like protein


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Atg9 transmembrane protein Atg9A and Atg9B required for autophagosomes formation ATM ataxia-telangiectasia mutated protein ATRA all trans-retinoic acid Autolysosome protein lysosomal-associated membrane protein 2 Autolysosome a compartment formed by the fusion of autophagosome with lysosome involved in the degradation of engulfed cell components. Autophagic body the inner membrane-bound structure of the autophagosome Autophagic flux the rate of cargo delivery to lysosomes through autophagy Autophagosome maturation events occurring post-autophagosome closure followed by delivery of the cargo to lysosomes Autophagosome a cytosolic double-membrane vesicle that engulfs cytoplasmic contents for delivery to the lysosome Autophagy inducers rapamycin, fluspirilene, trifluoperazine, pimozide, niguldipine, nicardipine, amiodarone, and loperamide Autophagy inhibitors chloroquine, hydroxychloroquine, and verteporfin Autophagy programmed cell death type 2, an ubiquitous process involved in health and disease AV autophagic vacuole Axonopathy degradation of axons in neurodegeneration BAD Bcl-2-associated agonist of cell death Bafilomycin A1(BAF-A1) an autophagy inhibitor Bafilomycin inhibitor of the vacular-type ATPase BAG Bcl-2-associated athanogene BAG3 Bcl2-associated athanogene 3 BAK Bcl-2 antagonist/killer BAP Bip-associated protein BAR domains crescent-shaped protein domains that bind to membranes Barkor Beclin-1-associated autophagy-related key regulator BATS Barkor/Atg14 (L) autophagosome targeting sequence BAX Bcl-2-associated X protein Bcl B-cell lymphoma BCL-2 B-cell CLL/lymphoma-2; Bcl-xL; B-cell lymphoma extra-large BCLAF1 Bcl 2-associated transcription factor 1 BCN1 Beclin 1 BCR B cell receptor Beclin 1 mammalian homolog of yeast Atg6, activating macroautophagy Beclin 1/Vps34/UVRAG complex positively contributes to autophagosome maturation and endocytic trafficking BH Bcl-2-homology BH3 Bcl-2 homology domain-3 BH3-only proteins induce macroautophagy BHMT betaine homocysteine methyltransferase protein found in the mammalian autophagosome (metabolic enzyme) BID BH3-interacting domain death agonist Bif-1 protein interacts with Beclin 1; required for macroautophagy BIF1 BAX-interacting factor 1 Bim Bcl-2 interacting mediator of cell death Bip ER-specific member of heat shock protein to family BNIP proapoptotic protein BNIP3 Bcl-2/adenovirus E1B 19-kDa protein-interacting protein 3; cell death–inducing mitochondrial protein Bortezomib selective proteasome inhibitor

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C1AP cellular inhibitor of apoptosis protein CaMKKβ protein activates AMPK at increased cytosolic calcium concentration CaMKs calcium-/calmodulin-dependent protein kinases CASA chaperone-assisted selective autophagy Caspases cysteine aspartic acid–specific proteases Cathepsins proteases located inside lysosomes at acid pH CCCP carbonyl cyanide m-chlorophenylhydrazone CCD coiled-coil domain CCI-779 rapamycin ester that induces macroautophagy CD46 glycoprotein mediates an immune response to invasive pathogens Cdk1 cyclin-dependent kinase 1 Chaperone a protein that assists other proteins in their folding, unfolding, and intracellular trafficking by preventing nonspecific interactions with other surrounding proteins Chloroquine an autophagy inhibitor which inhibits fusion between autophagosomes and lysosomes CHOP C/EBP homologous protein CIMR cation-independent mannose 6-phosphate receptor c-Jun mammalian transcription factor that inhibits starvation-induced macroautophagy Clg 1 a yeast cyclin-like protein that induces macroautophagy CMA chaperone-mediated autophagy: autophagic pathway through which cytosolic proteins are targeted (one by one) to the surface of the lysosome from where they reach the lumen by crossing the lysosomal membrane COG functions in the fusion of vesicles within the Golgi complex COP1 coat protein complex1 CP 20S core particle CPP calcium phosphate precipitate CPS carboxypeptidase S CRDs cysteine-rich domains CSCs cancer stem cells CTD carboxy-terminal domain CTGF connective tissue growth factor Cvt cytoplasm-to-vacuole targeting pathway in fungi DALIS DC aggresome-like structures DAMP damage-associated molecular pattern molecule DAP death-associated protein DAP1 death-associated protein 1 DAPK death-associated protein kinase DAPK1 death-associated protein kinase 1 Dcp-1 death caspase-1 DDR DNA damage response DEDD death effector domain–containing DNA-binding protein DEPTOR DEP domain containing mTOR-interacting protein DFCP1 a PtdIns (3) P-binding protein DISC death-inducing signaling complex DKO Box/Bak double knockout DMPK myotonic dystrophy protein kinase DMV double-membrane vesicle DOR diabetes-and obesity-regulated gene DRAM damage-regulated autophagy modulator DRAM1 damage-regulated autophagy modulator 1 induces autophagy in a p53-dependent manner.


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DRC desmin-related cardiomyopathy DRiP defective ribosomal protein DRips defective ribosome products Drp1 dynamin-related protein 1 dsRNA (double-stranded RNA) it is a molecule that mediates interference with the expression of specific genes in a number of organisms DUB deubiquitinases that accumulate proteins into aggresomes E2F1 a mammalian transcription factor ECD evolutionary conserved domain EEA1 early endosome antigen 1 eEF eukaryotic elongation factor EGFR epidermal growth factor receptor eIF eukaryotic initiation factor eIF2α eukaryotic initiation factor 2 alpha kinase EMA endosomal microautophagy: degradation of cytosolic proteins in late endosomes after internalization by mechanisms that resemble those in microphagy EMT epithelial-to-mesenchymal transition Endosomes early compartments fuse with autophagosomes to generate amphisomes ER stress loss of ER lumenal homeostasis ERAA endoplasmic reticulum–activated autophagy ERAD endoplasmic reticulum–associated degradation pathway ERK MAPK/extracellular signal-regulated protein kinase ERK1/2 extracellular signal-regulated kinase ½ ERN1 endoplasmic reticulum-to-nucleus signaling 1 ERQC endoplasmic reticulum quality control ERT enzyme replacement therapy ESCRT endosomal sorting complex required for transport Everolimus mTOR inhibitor F1P200 protein modulates ULK complex activity FADD Fas-associated protein with death domain FAK focal adhesion kinase FIP200 focal adhesion kinase family-interacting protein (200 kDa) FKBP12 FK506-binding protein 12 FLIP FADD-like antiapoptotic molecule FOXO forkhead box protein O FoxO3 forkhead box O transcription factor 3 FoxO3a (forkhead box O family member) a transcription factor that regulates expression of genes involved in oxidative stress, apoptosis, cell cycle transition, DNA repair, etc. FYCO1 FYVE and coiled domain containing 1 GAA acid α-glucosidase GABARAP gamma-aminobutyric acid receptor-associated protein GADD34 growth arrest and DNA damage-inducible protein 34 GAP GTPase-activating protein GAPDH glyceraldehyde-3-phosphate dehydrogenase GAS group A Streptococcus GATE-16 Golgi-associated ATPase enhancer of 16 kDa G-CSF granulocyte colony-stimulating factor GEF guanine nucleotide exchange factor GERL Golgi-ER-lysosome GFP green fluorescent protein Glycophagy degradation of glycogen particles GPCR G protein–coupled receptor

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GRASP Golgi reassembly stacking protein GRO growth-regulated oncogene GRP78 glucose-regulated protein, 78 kDa GSK-3β glycogen synthase kinase 3 beta regulates macroautophagy GST-BHMT BHMT fusion protein used to assay macroautophagy in mammalian cells HAV heavy autophagic vacuole HCV hepatitis C virus HDAC6 histone deacetylase 6, a central component of basal autophagy that targets protein aggregates and damaged mitochondria HDACs histone deacetylases HHAR1 human homolog of Drosophila ariadne 1 HIF hypoxia-inducible factor HIF1 hypoxia-inducible factor 1 HK histidine kinase acts on a single target HMGB1 high-mobility group box-1 HOP1 REV7 and MAD2 protein domains may recognize DNA damage related chromatin structures HOPS homotypic fusion and vacuole protein sorting HORMA Hop1p, Rev7p, and Mad2 Hrb HIV Rev-binding protein HR-PCD hypersensitive response programmed cell death hsc70 heat shock cognate protein of 70 kDa HSF1 heat shock transcription factor 1 HSP heat shock protein Hsp70 and Hsp90 heat shock molecular chaperones hspB1 heat shock protein β-1 hspB8 heat shock cognate protein β-8 HSV-1 herpes simplex virus type 1 I13P phosphatidylinositol IAP inhibitor of apoptosis protein ICAM-1 intercellular adhesion molecule-1 IDR intrinsically disordered region IGFBP3 insulin-like growth factor–binding protein 3 IGFH insulin-like growth factor 2 IGFIIR insulin-like growth factor 2 receptor Ikk inhibitor of nuclear factor κB IL3 interleukin-3 IM isolation membrane Immunoamphisomes amplify pathogen degradation in dendritic cells Inflammasomes multiprotein complexes containing one or more Nod-like receptors that are activated following cellular infection or stress and trigger capase-1 activation and maturation of IL-1β and IL-18 to engage innate immune defenses. IRE1 inositol requiring enzyme-1 IRE1α inositol requiring ER-to-nucleus signal kinase-1α IRF interferon regulatory transcription factor IRGM immunity-associated GTPase family M IRS insulin receptor substrate JNK c-jun N-terminal kinase KD kinase domain KRAS an oncogene induces autophagy in cancer cells LAMP lysosome-associated membrane protein


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LAMP1 lysosome marker lysosome-associated protein 1 LAMP2 lysosomal-associated membrane protein 2 LAMP-2A lysosomal-associated membrane protein 2A LAP LC3-associated phagocytosis LAV light autophagic vacole LC3 (MAP1LC3B) autophagosomes marker microtubule-associated protein 1 light chain 3b LC3 microtubule-associated protein 1 light chain-3 LC3-I soluble human microtubule-associated protein 1 light chain LC3-II LC3-phospholipid conjugate LET linear energy transfer Lipophagosomes autophagosomes containing lipid droplets Lipophagy selective delivery of lipid droplets for lysosomal degradation LIR LC3-interacting region LITAF lipopolysaccharide-induced tumor necrosis factor-alpha factor LKB liver kinase B LMP lysosomal-mitochondrial pathway LRP1 low-density lipoprotein receptor-related protein 1 LRRK2 leucine-rich repeat kinase 2 LSD lysosomal storage disorder Lysosome a single-membrane enclosed vesicle programmed to the degradation of cellular components for recycling, characterized by its acidic pH and abundance of hydrolases Lysosomotropic agents compounds that accumulate preferentially in lysosomes M1F macrophage migration inhibitory factor Macroautophagy (autophagy) autophagy pathway in which cytosolic proteins and organelles are sequestered into a double-membrane vesicle that fuses with a lysosome to assure their degradation Macrolipophagy regulation of lipid metabolism by autophagy MALS macroautophagy–lysosome system MAM mitochondria-associated ER membrane MAP microtubule-associated protein MAP3K MAP kinase kinase kinase MAP4K3 mitogen-activated protein kinase kinase kinase 3 MAPK mitogen-activated protein kinase MAPKAPK-2 MAP kinase-activated protein kinase 2 MAPLC3 microtubule-associated protein light chain MARF mitofusion mitochondrial assembly regulatory factor MBL mannose-binding lectin MBP myelin basic protein MCL1 myeloid cell leukemia sequence 1 (BCL2-related) MCP monocyte chemotactic protein MCU mitochondrial calcium uptake uniporter pore MDC monodansylcadaverine to measure autophagic flux in vivo Mdivi-1 mitochondrial division inhibitor-1 MEF mouse embryonic fibroblast MEK MAPK/ERK kinase MFG-E8 globule EGF factor 8 protein MFN2 mitofusin 2 is a mitochondrial outer membrane protein involved in fusion/fission to promote mitochondrial segregation and elimination MG-132 proteasomal inhibitor MHC major histocompatibility complex MHC-II class II major histocompatibility complex

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MiCa mitochondrial inner membrane calcium channel Microautophagy internalization of cytosolic proteins and organelles into lysosomes through invaginations of the lysosomal membrane, resulting in pinching off a single-membrane vesicles into the lysosomal lumen Micropexophagy or macropexophagy Peroxisome degradation by autophagic machinery MIM MIT-interacting motif MIPA micropexophagy-specific membrane apparatus miRNA (microRNA) a small noncoding RNA molecule (22 nucleotides) that functions in RNA silencing and posttranscriptional regulation of gene expression in as much as 30% of all mammalian protein-encoding genes. MIT microtubule interacting and transport Mitofusion mitochondrial fusion–promoting factor Mitophagy degradation of dysfunctional mitochondria MMP matrix metalloproteinase MMP mitochondrial membrane potential MOM mitochondrial outer membrane MOMP mitochondrial outer membrane permeabilization MPS mucopolysaccharidoses MPT mitochondrial permeability transition mPTP mitochondrial permeability transition pore mRFP monomeric red fluorescent protein MSD multiple sulfatase deficiency MSK1 mitogen- and stress-activated protein kinase 1 MTMR myotubularin-related protein MTMR3 myotubularin-related protein 3 inhibits autophagy MTOC microtubule-organizing center mTOR mammalian target of rapamycin that inhibits autophagy and functions as a sensor for cellular energy and amino acid levels mTORC1 mammalian target of rapamycin complex 1 MTP mitochondrial transmembrane potential MTS mitochondrial targeting sequence MVB multivascular body NAC N-acetyl-l-cysteine NADPH nicotinamide adenine dinucleotide phosphate; reduced NAF-1 nutrient-deprivation autophagy factor-1 NALP NACHT-LRR-PYD-containing protein NBR1 neighbor of BRCA1 gene NDP52 nuclear dot protein 52 kDa NEC-1 necrostatin-1 Necroptosis a form of programmed cell death by activating autophagy-dependent necrosis Necrosis cell death caused by a serious physical or chemical insult NES nuclear export signal NFκB nuclear factor kappaB Nix a member of the Bcl-2 family required for mitophagy NLRP3 nod-like receptor pyrin domain-containing 3 NLRs nucleotide-binding oligomerization domain-like receptors NLS nuclear localization signal Nod nucleotide-binding oligomerization domain Nodophagy node-mediated autophagy Noncanonical autophagy Beclin-1-independent autophagy NOS nitric oxide synthase NOX NADPH oxidase


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Nrf2 nuclear factor 2 OCR oxygen consumption rate Omegasome PI(3)P-enriched subdomain of the ER involved in autophagosome formation OMM outer mitochondrial membrane Oncosis (Greek for swelling) a cell death faster than apoptosis OPA1 mitafusin 1 is required to promote mitochondrial fusion Ox-LDL oxidized low-density lipoprotein is a major inducer of ROS, inflammation, and injury to endothelial cells P13K phosphatidylinositol-3-kinase p62 an autophagy substrate p62/SQSTM1 sequestosome 1 protein p70S6K ribosomal protein S6 PACRG Parkin coregulated gene PAD peptidylarginine deiminase PAMP pathogen-associated molecular pattern molecule PAS preautophagosomal structure; phagophore assembly site PB1 domain Phox and Bem1 domain PCD programmed cell death PCDs protein conformational disorders PCP protein correlation profiling PDI protein disulfide isomerase PDK pyruvate dehydrogenase kinase PDPK1 phosphoinositide-dependent protein kinase 1 PE phosphatidylethanolamine PERK ER-associated transmembrane serine/threonine protein kinase PERK protein kinase–like endoplasmic reticulum kinase PFI proteasome functional insufficiency PGAM5 phosphoglycerate mutase family member 5 Phagophore precursors single-membraned vesicles, the homotytic fusion of which leads to the formation of phagophore Phagophore isolated membrane formed by the hemolytic fusion of autophagic precursors and elongation of the phagophore leads to the formation of autophagosomes PI (3) K-PKB-FOXO a growth factor that inhibits autophagy and increases apoptosis by regulating glutamine metabolism PI3K phosphatidylinositol 3-kinase PI3KC3 class III phosphatidylinositol-3-kinase PINK1 PTEN (phosphatase and tensin homolog deleted on chromosome 10)-induced putative kinase 1 PKA protein kinase A PKB protein kinase B PKC protein kinase C PKR dsRNA-activated protein kinase polyQ polyglutamine PPAR peroxisome proliferator-activated receptor PQC protein quality control PRAS40 proline-rich AKT substrate 40 Primary lysosome a degradative organelle not involved as yet in degradation Prion disease transmissible spongiform encephalopathy Proteopathy refers to a class of diseases in which certain proteins become structurally abnormal, and thereby disrupt the function of cells, tissues, and organs of the body

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PRRs pathogen recognition receptors PSM proteasome subunit PSMB5 proteasome subunit beta type-5 PSV protein storage vesicle PtdIns phosphatidylinositol PtdIns(3)P phosphatidylinositol(3)phosphate PTGS posttranscriptional gene silencing PUMA p53 upregulated modulator of apoptosis Pyroptosis a cell death pathway associated with caspase 1 R1G retrograde signaling pathway Rag GTPase that activates TORC1 in response to amino acids RAGE receptor for advanced glycation end products Rapamycin a well-known autophagy inducer by suppressing mTOR RAPTOR regulatory-associated partner of mTOR RB1CC1 RB1-inducible coiled-coil protein 1 RE recycling endosome Residual body lysosome containing undegraded material Reticulophagy degradation of endoplasmic reticulum RFP red fluorescent protein Ribophagy degradation of ribosomes RIP receptor-interacting protein RIPK1 receptor-interacting protein kinase 1 RISC RNA-induced silencing complex RLS reactive lipid species RNAi RNA interference RNS reactive nitrogen species ROS reactive oxygen species ROT Rottlerin used as a protein kinase C-delta inhibitor RP 19S regulatory particle RR response regulator that functions directly as a transcription factor RTK receptor tyrosine kinase RT-PCR real-time polymerase chain reaction Rubicon RUN domain and cysteine-rich domain-containing Beclin-1-interacting protein SAPKs stress-activated protein kinase SASP senescence-associated secretory phenotype Secondary lysosome a degradative organelle involved in degradation Selective Autophagy selective recruitment of substrates for autophagy Sequestosome (SQSTMI)1 p62 protein, a ubiquitin-binding scaffold protein Sequestosome 1 (p62/SQSTM1) a multifunctional adapter protein implicated in tumorigenesis Sequestosome1 an autophagy substrate SESN2 sestrin-2 shRNA short hairpin RNA siRNA (small-interfering RNA) a small RNA molecule that silences genes at the transcriptional, posttranscriptional, and/or translational levels SIRT1 a NAD+-dependent histone deacetylase smARF small mitochondrial ARF SMIR small molecule inhibitor of rapamysin SNARE soluble N-ethylmaleimide–sensitive factor attachment protein receptor SNP single nucleotide polymorphism SOD superoxide dismutase SQSTM1 sequestosome 1 ssRNA single-stranded RNA


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STAT1 signal transducer and activator of transcription 1 STK11 serine/threonine kinase 11 STX17 syntaxin 17 SUMO small ubiquitin-related modifer Syt1 synaptotagmin1 T1DM type 1 diabetes mellitus TAB TAK1-binding protein TAK1 transforming growth factor β-activated kinase 1 TAKA transport of Atg9 after knocking out Atg1 TASCC TOR-autophagy spatial coupling compartment TBK Tank-binding kinase-1 TCN transe-Golgi network TCR T-cell receptor TCS represents the primary signaling modality in bacteria TECPR1 tectonin beta-propeller repeat containing 1 Tensirolimus mTOR inhibitor TFEB transcript factor EB TGFβ transforming growth factor β that activates autophagy TGN trans-Golgi network Thapsigargin an inhibitor of autophagy by blocking autophagosomal fusion with lysosomes TIGAR TP53 (tumor protein 53)–induced glycolysis and apoptosis regulator TK tyrosine kinase TKI tyrosine kinase inhibitor Tlg t-SNARE affecting a late Golgi compartment TLR toll-like receptor TMD transmembrane domain TMEM166 transmembrane protein 166 that induces autophagy TNF tumor necrosis factor TNF-α tumor necrosis factor-alpha Torin1 ATP-competitive mTOR inhibitor TP53INP2 tumor protein p53-induced nuclear protein 2 TRADD tumor necrosis factor receptor type 1-associated death domain protein TRAF2 tumor necrosis factor receptor-associated factor 2 TRAF6 tumor necrosis factor receptor-associated factor 6 TRAIL tumor necrosis factor-regulated apoptosis-inducing ligand Trehalose a disaccharide that influences protein folding, protecting cells against various environmental stresses by preventing protein denaturation TSC tuberous sclerosis complex TSC2 tuberous sclerosis complex 2 TSG tumor suppressor gene TSG101 tumor suppressor gene 101 TSPO tryptophan-rich sensory protein Ub ubiquitin Ub1 ubiquitin-like UBA ubiquitin-associated UBAN ubiquitin-binding domain Ubiquitin a small protein that functions in intracellular protein breakdown and histone modification Ubiquitination a well-established signal for inducing autophagy of protein aggregates UCPs uncoupling proteins located in the mitochondrial inner membrane ULK Unc-51-like kinase complex ULK uncoordinated-51-like kinase

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ULK1 and ULK2 proteins mediate mTOR signaling and Atg9 cycling ULK1 putative mammalian homolog of Atg1p UPR unfolded protein response UPS ubiquitin-proteasome system UVRAG UV irradiation resistance-associated tumor suppressor gene VAchT vesicular acetylcholine transporter Vacuole a “lysosome” in plants and fungi involved in degradation, storage, and osmoregulation VAMP vesicle-associated membrane protein VAMP8 vesicle-associated membrane protein 8 VAPB vesicle-associated membrane protein-associated protein B VCP/p97 valosin-containing protein involved in endosomal trafficking and autophagy VDAC voltage-dependent anion channel VDAC1 voltage-dependent anion-selective channel protein 1 VEGF vascular endothelial growth factor VEGFR vascular endothelial growth factor receptor VMP1 vacuole membrane protein 1 VPS vacuolar protein sorting vps15 vacuolar protein sorting 15 homolog vps34 vacuolar protein sorting 34 VT1 vesicles transport through interaction with t-SNARE homolog VTAs vascular targeting agents VTC vacuolar transporter chaperone WIP1 WD-repeat protein-interacting phosphoinositides Wortmannin an autophagic inhibitor XBP1 a component of the ER stress response that activates macroautophagy Xenophagy degradation of invading bacteria, viruses, and parasites YFP yellow fluorescent protein Ypt1 yeast protein transport 1 Zymophagy lysosomal degradation of zymogen granules (digestive enzymes)

Note For more information, please see the following articles: Klionsky, D.J., Codogno, P., Cuervo, A.M., et al., 2010. A comprehensive glossary of autophagy-related molecules and processes. Autophagy 6, 438–448. Klionsky, D.J., Bachrecke, E.H., Brumell, J.H., et al., 2011. A comprehensive glossary of autophagy-related molecules and processes (2nd edition). Autophagy 7 (4), 1273–1294. Klionsky, D.J., Abdalla, F.C., Abeliovich, H., et al., 2012. Guidelines for the use and interpretation of assays for monitoring autophagy. Autophagy 8 (4), 445–544.

Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A A2E, 113–114 AB. See Amyloid beta (AB) Abnormal proteins, 24–26 Acetylation, 160 Activating transcription factor 6 (ATF6), 13 Active transcription factor 4 (ATF4), 251 Acute kidney injury (AKI), 241 Acyl coenzyme A (CoA), 63 AD. See Alzheimer’s disease (AD); Amyloid protein (AD) Adapter proteins (AP2), 18 Adaptive immunity, 310–311 Adaptor proteins through ubiquitin-binding protein (UBA), 32 Adenosine monophosphate-activated protein kinase (AMPK), 40–41, 48, 98–99, 126–127, 246–247, 250, 279, 293, 304 Adenosine triphosphatase (ATPase), 107 Adenosine triphosphate (ATP), 238 2-AG. See 2-Arachidonoylglycerol (2-AG) Age-related macular degeneration (AMD), 111 Aggrephagy, 31–33. See also Autophagy aggresome, 32 autophagic systems, 32 ubiquitin proteasome, 32 Aggresome, 23, 31–32 Aggresome-like structures (ALS), 23 Aging, 4–5, 39–46 cellular senescence in, 43–44 AD, autophagy in, 45 autophagy to dietary restriction, 42 HD, autophagy in, 45 heart disease, autophagy in, 45 macular degeneration, autophagy in, 45–46 mTOR, 41–42 response by mTOR, 42 sirtuins, 42–43 stem cells, 43 process, 41 in RPECs, 112–113 on skeletal muscle, 44 AIF. See Apoptosis-inducing factor (AIF) AIM. See Atg8 family interacting motif (AIM) AIM/LIR. See Atg8-interacting motif/LC3-interacting region (AIM/LIR)

AKI. See Acute kidney injury (AKI) Alcohol, 5 Alcoholic liver disease, 5 ALFY protein. See Autophagy-linked FYE protein (ALFY protein) Allophagy, 58–59 αB-crystallin, 114–115 and autophagy, 114–115 in RPECs, 115 α-crystallins, 114–115 Alpha-synuclein, 50, 63–64, 73 ALR. See Autophagic lysosome reformation (ALR) ALS. See Aggresome-like structures (ALS); Amyotrophic lateral sclerosis (ALS) Alzheimer’s disease (AD), 5, 96–97, 160, 168 autophagy in, 45 HDAC inhibitors, 173–174 AMBRA-1. See Autophagy/beclin-1 regulator 1 (AMBRA-1) AMD. See Age-related macular degeneration (AMD) AMPK. See Adenosine monophosphate-activated protein kinase (AMPK) Amyloid beta (AB), 5 peptide, 168 Amyloid deposits, 26 Amyloid precursor protein (APP), 49, 168 Amyloid protein (AD), 73 Amyotrophic lateral sclerosis (ALS), 50 Anticancer agent, C-8 cationic lipid containing estradiol, 281 Antigen-presenting cells (APCs), 310 AP2. See Adapter proteins (AP2) Apaf-1. See Apoptotic protease activating factor-1 (Apaf-1) APCs. See Antigen-presenting cells (APCs) Apoptosis, 270–273, 271f, 282–284, 283f apoptotic stimuli, 51–52 cross talk between autophagy and, 51–55 cross talk between autophagy and, 274–276 ER and, 27 ESC8treatment leads, 285 extrinsic pathway, 272 intrinsic pathway, 272 Apoptosis-inducing factor (AIF), 51–52 Apoptotic protease activating factor-1 (Apaf-1), 13, 272

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334

Index

APP. See Amyloid precursor protein (APP) 2-Arachidonoylglycerol (2-AG), 7 Arginine, 224 starvation, 60–61 Argininosuccinate synthetase 1 (ASS1), 60 Aspergillus fumigates, 316 ASS1. See Argininosuccinate synthetase 1 (ASS1) Ataxia Telangiectasia mutated and Rad3 related kinase (ATR kinase), 214 Ataxia Telangiectasia mutated kinase (ATM kinase), 214, 228 autophagy and senescence, 228–229 autophagy regulation of DDR, 229–230 ATF4. See Active transcription factor 4 (ATF4) ATF6. See Activating transcription factor 6 (ATF6) ATG. See AuTophaGy (ATG) Atg8 family interacting motif (AIM), 64 Atg8-interacting motif/LC3-interacting region (AIM/ LIR), 223 Atgs. See Autophagy-related genes (Atgs) Atherosclerosis, 260–262 XBP-1 in, 264 ATM kinase. See Ataxia Telangiectasia mutated kinase (ATM kinase) Atomic force microscopy, 24 ATP. See Adenosine triphosphate (ATP) ATPase. See Adenosine triphosphatase (ATPase) ATR kinase. See Ataxia Telangiectasia mutated and Rad3 related kinase (ATR kinase) ATR-interacting protein (ATRIP), 216–217 Autoimmunity autoimmune disorders, 207 autophagy-related genes in, 311–313 Crohn’s disease, 311–312 SLE, 312 Autophagic lysosome reformation (ALR), 17–18 Autophagometer, 94 Autophagosomes, 60, 111–112, 134, 146, 166, 196, 261 construction mechanism, 273–274 flux, 92, 94–96 measuring autophagic flux, 93–96, 95f modeling autophagy system, 98–101 quantifying autophagic flux, 96–97 formation, 15–16 membranes, 184–185 Atg9 recycling from, 188–189 AuTophaGy (ATG), 304 Autophagy, 4–5, 14, 92–93, 96, 98–99, 111–112, 121, 129, 134, 166, 182, 196, 207, 214, 228–229, 231f, 237–238, 246, 251, 253, 261–262, 273–274, 291–293, 309, 311. See also Aggrephagy; Selective autophagy addiction, 19

AKI, 242 alcohol, 5 αB-crystallin and, 114–115 Atg9 structure and role, 183–184 in autoimmunity, 311–313 Crohn’s disease, 311–312 SLE, 312 autophagosome formation, 15–16 autophagy-suppressing drug, 241–242 cancer-promoting action, 238–240 cancer-suppressing action, 240–241 cell death, 251 induction by ESC8, 284–285 and cellular senescence in aging, 39–46 cigarette smoking, 5 classical, 294f clearance, 170–171 cross talk between apoptosis and, 51–55, 274–276 DDR in higher eukaryotes, 215–218 degrades lipids in liver, 121f and DNA damage, 225–230 as double-edged sword, 18–19 DSB repair, 218–220 dysfunction, 96 ER, 11–13 as evolutionarily conserved survival mechanism, 304–305 in explosive phase, 8 failsafe mechanism, 135–136 flux, 6, 16–17, 198, 199f, 200f tandem GFP-RFP-LC3 to assess, 202 functions, 9–10 in heart disease, 48–49 and immune system, 37–39 inevitable death, 8 inhibition in regulating hepatic lipid metabolism metabolic disorders, 120 molecular switch, 126–129 proteasome linking autophage and lipid metabolism, 123–126 SirT1 as nutrient/metabolic sensor, 127 in intracellular bacterial infection, 47 involvement in RPECs demise, 114 of iron-binding proteins in RPECs, 113 lysosome reformation, 17–18 machinery, 94–96, 305–313 effects between innate and adaptive immunity, 310–311 in innate immune mechanisms of pathogen elimination, 307–308 regulation of innate immune signaling pathways by, 308–310 markers, 125

Index

mechanism of autophagosome construction, 273–274 membrane remodeling in, 146 methods of measuring in disease, 198–204 in vitro methods, 198–203 in vivo methods, 203 mitochondrial fusion and fission, 56 mitotic autophagy, 135–136 monitoring, 33 monitoring nonclassical substrate of, 136–138 mTOR, 34–35 necroptosis and, 55 in neurodegenerative diseases, 49–51 in normal mammalian cells, 10–11 pathway in higher eukaryotes, 220–225, 222t pathways, 166 physical exercise, 6 process, 10 proteins, 16, 25, 28–31, 127 Bcl-2, 29 microtubule-associated LC3, 30–31 nonautophagic functions of autophagy-related proteins, 29–30 protein degradation systems, 28–29 synthesis, 19–28 RAB-GAPs involved in, 151–152 Rab3GAP1 and Rab3GAP2, 151 TBC1D2/Armus, 147 TBC1D5, 147–148 TBC1D14, 148–149 TBC1D15 and TBC1D17, 149 TBC1D25/OATL1, 150–151, 150f receptors, 313–314 regulates protein turnover, 134–135 in regulating cyclin A2 degradation, 134 regulation of DDR, 229–230 in yeast and mammals, 221–223 REGγ-SirT1 regulates lipid metabolism by modulating, 127–129 in retinal homeostasis, 112 ROS, 33–34 in RPE, 111–114 aging and autophagy in RPECs, 112–113 retinal pathologic conditions and autophagy of RPECs, 113 in RPECs in experimental systems, 113–114 homeostasis, 112 and senescence, 39 systems, 32 in tumorigenesis and cancer, 35–37 types of, 13–15 ubiquitination and, 55

335

to ultraendurance exercise, 7 in viral defense and replication, 46–47 XBP-1 in, 264 Autophagy related proteins. See Autophagy-related genes (Atgs) Autophagy-deficient mice, 240–241 Autophagy-linked FYE protein (ALFY protein), 57 Autophagy-lysosomal pathway, 166 Autophagy-related genes (Atgs), 16, 25, 28, 37, 50, 111–112, 127, 182, 186–187, 196, 246, 292 Atg1, 246 Atg1ULK1/ULK2, 221 kinase complex, 182 Atg4c, 171 Atg5, 96 Atg7, 138 Atg8, 57–58 Atg8p-PE conjugation system, 69 Atg9, 182, 183f, 221 in autophagy, 183–184 physical interaction partners, 184t recycling, 188–189 roles at preautophagosomal structure, 187–188 trafficking via ER and Golgi compartments, 184–186, 185f vesicles, 186–187 Atg12, 275 Atg12-Atg5 signaling molecule, 10–11 Atg14 proteins, 304–305 Autophagy-suppressing chloroquine, 241 drug, 241–242 hydroxychloroquine, 241 Autophagy/beclin-1 regulator 1 (AMBRA-1), 221–223 Axonal transport, 163 Axonophagy, 59–60

B B-crystallin, 114–115 Bacillus Calmette–Guérin (BCG), 307 Bacterial xenophagy, 298 Bafilomycin A1 (BFA), 94, 137–138, 251 Basal cell carcinoma (BCC), 250–251 Basal control autophagy, 10 Basic leucine zipper domain (bZIP domain), 262 BAT. See Brown adipose tissue (BAT) BCC. See Basal cell carcinoma (BCC) BCG. See Bacillus Calmette–Guérin (BCG) Bcl2 homology 3 domain (BH3D), 26 BCL2-beclin 1 complex, 6 BDNF. See Brain–derived neurotrophic factor (BDNF) Beclin 1, 8, 29, 237–238, 252, 264–266 heterozygous disturbance of, 240

336 BECN-1 gene, 36 BFA. See Bafilomycin A1 (BFA) BH3D. See Bcl2 homology 3 domain (BH3D) BMCs. See Bone Marrow cells (BMCs) Bone Marrow cells (BMCs), 207 Bortezomib, 18–19 Brain–derived neurotrophic factor (BDNF), 109 Breast cancer, 276 ESC8mediates intrinsic apoptotic pathway in breast cancer cell lines, 282–284 Brown adipose tissue (BAT), 122 Bruch membrane, 108 Budding yeast, DDR in, 218 bZIP domain. See Basic leucine zipper domain (bZIP domain)

C C-8 cationic lipid containing estradiol as anticancer agent, 281 C-terminal domain (CTD), 247 Caenorhabditis elegans, 40, 42, 147, 275 Caloric restriction (CR), 7 Calpain 1, 10–11 Cancer, 165–166, 204 autophagy in, 35–37 cancer-promoting action of autophagy, 238–240 cancer-suppressing action of autophagy, 240–241 cell, 238 expression of ULK1 in, 250–251 therapeutic strategy for targeting ULK1 in, 253–255, 254f Canonical autophagy, 313 Carboxyl terminus of Hsp70-interacting protein (CHIP), 6 Carboxylates, 163 Cargo flux, 92 receptors, 134 sequestration, 14 CBP. See CREB-binding protein (CBP) Cdc2. See Cell division cycle protein 2 (Cdc2) CDKs. See Cyclin-dependent kinases (CDKs) Cell division cycle protein 2 (Cdc2), 279–280 Cells, 270 cell cycle, PI3K-AKT-mTOR pathway, 279–280 cell proliferation, PI3K-AKT-mTOR pathway, 279–280 cell survival, P53-mTOR pathway, 280–281 cell-type dependent, 266 death, 270 P53-mTOR pathway, 280–281 PI3K-AKT-mTOR signaling, 278–279 receptor pathways, 51

Index

division, 135 cycle, 133–134 nucleus, 68–69 Cellular events, 68–69 homeostasis, 273 junctions, 108 mechanism, 17 proteins, 21–22 Cellular senescence, 39 in aging, 39–46 AD, autophagy in, 45 aging on skeletal muscle, 44 autophagy to dietary restriction, 42 HD, autophagy in, 45 heart disease, autophagy in, 45 macular degeneration, autophagy in, 45–46 mTOR, 41–42 response by mTOR, 42 sirtuins, 42–43 stem cells, 43 roles, 43–44 cGAMP. See Cyclic GMP-AMP (cGAMP) cGAS. See Cyclic GMP–AMP synthase (cGAS) Chaperone Hsp70 proteins, 11 Chaperone-dependent autophagy, 166 Chaperone-mediated autophagy (CMA), 13–15, 24, 96–97, 121, 196, 223–224, 246, 292 Chemotherapy, 242 CHIP. See Carboxyl terminus of Hsp70-interacting protein (CHIP) Chloroquine (CQ), 94, 206–207, 241, 251 Chondrostereum fungus, 53–54 Choroidal neovascularization (CNV), 110 Chromatophagy, 60–61 Chronic infl ammatory bowel diseases (IBD), 311–312 Chronic obstructive pulmonary disease (COPD), 5 Cigarette smoking, 5, 110 Cilia, 61 Ciliophagy, 61–62 Class I HDACs, 161–162 Class II HDACs, 162–163 Class III HDACs, 163 Class IV HDACs, 163 Clathrin, 18 CMA. See Chaperone-mediated autophagy (CMA) CNV. See Choroidal neovascularization (CNV) CoA. See Acyl coenzyme A (CoA) COG tethering complex. See Conserved oligomeric Golgi tethering complex (COG tethering complex) Colchicine, 94

Index

Colorectal cancer (CRC), 250–251 Conserved oligomeric Golgi tethering complex (COG tethering complex), 187 COPD. See Chronic obstructive pulmonary disease (COPD) Corticotrophin-releasing factor (CRF), 5 Coxiella burnetii, 308 CPD. See Cyclobutane pyrimidine dimers (CPD) CQ. See Chloroquine (CQ) CR. See Caloric restriction (CR) CRC. See Colorectal cancer (CRC) CREB-binding protein (CBP), 161 CREB-regulated transcription coactivator 2 (CRTC2), 127 CRF. See Corticotrophin-releasing factor (CRF) Crinophagy, 62, 206 Crohn’s disease, 12, 292, 311–312 Cross talk between apoptosis and autophagy, 274–276 extrinsic apoptosis–autophagy, 275–276 intrinsic apoptosis–autophagy, 275 complex, 225–230 CRTC2. See CREB-regulated transcription coactivator 2 (CRTC2) CTD. See C-terminal domain (CTD) CVT pathway. See Cytoplasm-to-vacuole transport pathway (CVT pathway) Cyclic GMP-AMP (cGAMP), 309 Cyclic GMP–AMP synthase (cGAS), 309 Cyclin A2, 133–134, 136–138 cyclin A2-EGFP, 136–137 degradation, 134, 136–138 autophagy in regulating, 134 autophagy regulates protein turnover, 134–135 mitotic autophagy, failsafe mechanism, 135–136 Cyclin-dependent kinases (CDKs), 133–134, 217, 279–280 Cyclobutane pyrimidine dimers (CPD), 230 Cytochrome, 261 Cytochrome c, 51–52 Cytokines, 109 Cytometry–based assays, 202 Cytoplasm-to-vacuole transport pathway (CVT pathway), 70, 182, 223, 247 Cytoplasmic elements, 106–107 Cytoprotective autophagy. See Autophagy, cell death Cytoskeletons, 108 Cytosolic Salmonella bacteria, 297 Cytotoxic autophagy. See Autophagy, cell death

D d-ATP. See Deoxy-ATP (d-ATP) DAF-16-FOXO transcription factor, 42

337

Damage-regulated modulator of autophagy-1 (DRAM1), 226 DAPK. See Death-associated protein kinase (DAPK) DCs. See Dendritic cells (DCs) DDR. See DNA damage response (DDR) Death-associated protein kinase (DAPK), 12, 53 DAPK1, 226 Death-inducing signaling complex (DISC), 272 Dendritic cells (DCs), 309 Deoxy-ATP (d-ATP), 272 Deoxyribonucleotides (dNTPs), 230 DEP domain containing mTOR-interacting protein (DEPTOR), 279 Deubiquitinating enzymes (DUBs enzymes), 55 DFCP1. See Double FYVE domain-containing protein 1 (DFCP1) DIABLO. See Direct inhibitor of apoptosis-binding protein (DIABLO) Dictyostelium discoideum, 63, 305–306 Diet, 7 Dietary factors, 7 Dietary restriction, autophagy to, 42 Direct inhibitor of apoptosis-binding protein (DIABLO), 51–52 DISC. See Death-inducing signaling complex (DISC) Disease, 204–207 autoimmune disorders, 207 autophagy genes associated with human disease, 197t cancer, 204 disease-causing proteins, 160, 167 emerging trends, 207–208 infectious diseases, 205–206 metabolic diseases, 206–207 methods of measuring autophagy in disease, 198–204 myopathies, 206–207 neurodegeneration, 204–205 Dishevelled degradation (Dvl degradation), 134 Disulfide isomerase, 11 DNA damage autophagy and, 225–230 ATM, 228 induced autophagy pathway, 226–228 checkpoint, 214–215, 216t pathways of GTA, 227f signaling, 216–217 trigger, 240 types, 215 DNA damage response (DDR), 214 autophagy regulation, 229–230 in higher eukaryotes DDR in budding yeast, 218 repair of DNA damage, 218 types of DNA damage, 215

338

Index

DNA damage–induced autophagy, 215 dNTPs. See Deoxyribonucleotides (dNTPs) Double FYVE domain-containing protein 1 (DFCP1), 11–12 Double-edged sword, autophagy as, 18–19 Double-membrane autophagosomes, 196 Double-strand breaks (DSBs), 215 repair, 218–220 homologous recombination, 219–220 NHEJ, 219 DR5. See TRAIL receptor 5 (DR5) DRAM1. See Damage-regulated modulator of autophagy-1 (DRAM1) Drosophila, 40, 174–175 D. melanogaster, 206–207 DSBs. See Double-strand breaks (DSBs) Dual finger mechanism, 144 DUBs enzymes. See Deubiquitinating enzymes (DUBs enzymes) Dvl degradation. See Dishevelled degradation (Dvl degradation) Dynein light chain1 (DYNL1), 275

E E-cadherin, 147 functions, 147 E3-ubiquitin ligases, 32 Early-endosomal antigen 1 (EEA1), 295–296 ECM. See Extracellular matrix (ECM) ECM metalloproteinase inducer (EMMPRIN), 107 ECs. See Endothelial cells (ECs) EEA1. See Early-endosomal antigen 1 (EEA1) EGCG. See Epigallocatechin gallate (EGCG) elF2. See Eukaryotic initiation factor 2 (elF2) ELISA. See Enzyme-linked immunosorbent assays (ELISA) Emerging trends, 207–208 EMMPRIN. See ECM metalloproteinase inducer (EMMPRIN) EMT. See Epithelial–mesenchymal transition (EMT) EndoG. See Endonuclease G (EndoG) Endogenous LC3, 33 Endonuclease G (EndoG), 51–52 Endoplasmic reticulum (ER), 10–13, 26–27, 72, 144, 182, 304 and apoptosis, 27 ATG9 trafficking via, 184–186 eukaryotic cells, 11–12 hepatitis B virus, 12 negative cancer cells, ESC8, 281–282 stress, 12–13, 27, 251 response, 263–264

Endostatin, 265 Endothelial cells (ECs), 262 XBP-1 in, 264 Endothelial monolayer, 260 Endothelial nitric oxide synthase (eNOS), 260 Enteritidis, Salmonella, 293–295 Enzyme-linked immunosorbent assays (ELISA), 207–208 Epigallocatechin gallate (EGCG), 66 Epithelial–mesenchymal transition (EMT), 278–279 EPO. See Erythropoietin (EPO) ER. See Endoplasmic reticulum (ER) ER protein oxidase 1 (Ero1), 23 ER-associated degradation (ERAD), 12 ER-to-nucleus signal: img 1 (IERN1), 13 ERAD. See ER-associated degradation (ERAD) ERE. See Estrogen receptor element (ERE) ERK1/2. See Extracellular signal–regulated kinases 1/2 (ERK1/2) Ero1. See ER protein oxidase 1 (Ero1) Erythropoietin (EPO), 109 ESC8, 281, 282f, 286f ER negative cancer cells, 281–282 ESC8-PI3K-AKT-mTOR pathway, 285 mediates intrinsic apoptotic pathway in breast cancer cell lines, 282–284 induction of autophagic cell death, 284–285 potent anticancer agent against ER-positive, 281–282 treatment leads to apoptosis and tumor regression, 285 Escherichia coli, 316 Estrogen receptor element (ERE), 276–278 Eukaryotes, 313 autophagy pathway in higher, 220–225, 222t autophagy regulation in yeast and mammals, 221–223 CMA, 224 mitophagy, 223–224 pexophagy, 224 selective autophagy, 223 DDR in higher, 215–218 Eukaryotic cells, 11–12, 144 Eukaryotic initiation factor 2 (elF2), 12 Exercise, 6–7 Exogenous oxidants, 110 Exophagy, 62–64 Extracellular aggregates, 168 Extracellular matrix (ECM), 106–107 Extracellular signal–regulated kinases 1/2 (ERK1/2), 113–114 Extrinsic apoptosis–autophagy, 275–276 Extrinsic pathway of apoptosis, 272

Index

F FAD. See Flavin adenine dinucleotide (FAD) Failsafe mechanism, 135–136 FAK. See Focal adhesion kinase (FAK) Family interacting protein of 200 KDa (FIP200), 246–247 Faslodex, 287 Fatty acids, 122 FFAs. See Free fatty acids (FFAs) FGF1. See Fibroblast growth factor 1 (FGF1) Fibroblast growth factor 1 (FGF1), 62–63 FIP200. See Family interacting protein of 200 KDa (FIP200) FK506-binding protein 12-rapamysin-associated protein 1 (FRAP1), 34 Flavin adenine dinucleotide (FAD), 23 FLIM. See Fluorescence lifetime imaging microscopy (FLIM) FLIP, 275–276 Flow cytometry–based methods, 202 Fluorescence lifetime imaging microscopy (FLIM), 136 Fluorescence resonance energy transfer (FRET), 136 Fluorescence-based techniques, 94–96 Focal adhesion kinase (FAK), 246–247, 276–278 Forkhead box O1 (FOXO1), 127 Förster resonance energy transfer. See Fluorescence resonance energy transfer (FRET) FOXO1. See Forkhead box O1 (FOXO1) FRAP1. See FK506-binding protein 12-rapamysinassociated protein 1 (FRAP1) Free fatty acids (FFAs), 121 FRET. See Fluorescence resonance energy transfer (FRET) Functional heterogeneity, 107 Functional polarity, 107

G GA. See Geographic atrophy (GA) GaAsP. See Gallium–arsenide–phosphide (GaAsP) GABARAPs. See γ-Aminobutyric acid receptorassociated proteins (GABARAPs) Gallium–arsenide–phosphide (GaAsP), 136–137 γ-Aminobutyric acid receptor-associated proteins (GABARAPs), 10 GAPs. See GTPase-associated proteins (GAPs) GAS. See Group A Streptococcus (GAS) GBP. See Guanylate-binding protein (GBP) Gcn5-related N–acetyltransferase superfamily members, 161 GEFs. See Guanine-nucleotide exchange factors (GEFs) GEMMs. See Genetically engineered mouse models (GEMMs) Gene expression, 169 Genetic mutations, 168

339

Genetically engineered mouse models (GEMMs), 204 Genome integrity, 214 Genome-wide association studies (GWAS), 311 GenoToxin stress–induced Autophagy (GTA), 226 Geographic atrophy (GA), 111 GFP-LC3, 33 Glucocorticoid receptor (GR), 278 Glucose transporters, 109 Glutamine, 224 Glutaredoxins (Grx), 110–111 Glutathione (GSH), 110–111 Glycogen, 64 autophagy, 206–207 Glycogen synthase (GlyS), 206–207 Glycophagy, 64 GlyS. See Glycogen synthase (GlyS) GM-CSF. See Granulocyte-macrophage colony stimulating factor (GM-CSF) Golgi compartments, ATG9 trafficking via, 184–186 Golgi complex, 11 Golgi reassembly and stacking protein (GRASP), 63 GR. See Glucocorticoid receptor (GR) Granulocyte-macrophage colony stimulating factor (GM-CSF), 109 GRASP. See Golgi reassembly and stacking protein (GRASP) GRO. See Growth-regulated protein (GRO) Group A Streptococcus (GAS), 297 Growth-regulated protein (GRO), 109 Grx. See Glutaredoxins (Grx) GSH. See Glutathione (GSH) GTA. See GenoToxin stress–induced Autophagy (GTA) GTPase-associated proteins (GAPs), 57, 144 Guanine-nucleotide exchange factors (GEFs), 72, 144, 184–185 Guanylate-binding protein (GBP), 308 GWAS. See Genome-wide association studies (GWAS)

H HAP1. See Huntingtin-associated protein-1 (HAP1) HATs. See Histone acetyltransferases (HATs) HBV. See Hepatitis B virus (HBV) HCC. See Hepatocellular carcinoma (HCC) HCV. See Hepatitis C virus (HCV) HD. See Huntington’s disease (HD) HDAC. See Histone deacetylase (HDAC) HDACI. See Histone deacetylase inhibitor (HDACI) Head and neck squamous cell carcinoma (HNSCC), 251 Heart disease, autophagy in, 45, 48–49 Heat shock cognate 70 (hsc70), 14–15 Heat shock proteins (Hsps), 26 Hsp70, 14–15 Helicobacter pylori, 53

340

Index

Hepatic lipid metabolism, autophagy inhibition in autophagy degrades lipids in liver, 121f metabolic disorders, 120 molecular switch, 126–129 proteasome linking autophage and lipid metabolism, 123–126 REGγ regulates, 124–125 Hepatitis B virus (HBV), 314 Hepatitis C virus (HCV), 47, 314 Hepatocellular carcinoma (HCC), 250–251 Hepatocellular carcinoma cells (HepG2 cells), 124–125 Hepatocyte growth factor (HGF), 109 HepG2 cells. See Hepatocellular carcinoma cells (HepG2 cells) HFD. See High-fat diet (HFD) HGF. See Hepatocyte growth factor (HGF) HIF. See Hypoxia-inducible factor (HIF) High-fat diet (HFD), 124–125 High-throughput screening (HTS), 253 Histone acetyltransferases (HATs), 160 Histone deacetylase (HDAC), 42–43 class I, 161–162 class II, 162–163 class III and IV, 163 enzymes, 160–163, 162t HDAC6, 31, 163 Histone deacetylase inhibitor (HDACI), 49, 160, 163–166, 164t cancer vs. neurodegenerative disorders, 165–166 histones and HDAC enzymes, 160–163 protein folding disorders, 167–169 proteopathies, 167–169 in proteopathies, 169–176 UPS and autophagy pathways, 166 Histones, 160–163 HNSCC. See Head and neck squamous cell carcinoma (HNSCC) Homeostasis, 237–238 Homo sapiens, ULK1 in, 249f Homologous recombination (HR), 218–220 Host defense against Salmonella, intestinal autophagy in, 297–299, 299f HR. See Homologous recombination (HR) hsc70. See Heat shock cognate 70 (hsc70) Hsps. See Heat shock proteins (Hsps) HTS. See High-throughput screening (HTS) htt. See Huntingtin (htt) HTT. See Huntington (HTT) Human autoimmune diseases, 317 Human genetics studies, 151 Huntingtin (htt), 45 clearance, 170–171 mutant, 50 protein, 73

Huntingtin-associated protein-1 (HAP1), 45 Huntington (HTT), 167 Huntington’s disease (HD), 50, 96–97, 160, 167–173. See also Parkinson’s disease (PD) autophagy and Htt clearance, 170–171 autophagy role in, 45 ubiquitination-related gene expression in response, 171–173, 172t Hydrogen peroxide (H2O2), 313 Hydroxamic acids, 163 Hydroxychloroquine, 18–19, 97, 241 Hypoxia-induced autophagy, 239–240 Hypoxia-inducible factor (HIF), 237–238

I IBD. See Chronic infl ammatory bowel diseases (IBD) ICs. See Immune complexes (ICs) IDRs. See Intrinsically disordered regions (IDRs) IERN1. See ER-to-nucleus signal: img 1 (IERN1) IGF-1. See Insulin-like growth factor (IGF-1) IHC. See Immunohistochemistry (IHC) IkB kinase activation (IKK activation), 171 IL. See Interleukin (IL) Immune complexes (ICs), 315 Immune system, autophagy and, 37–39 Immunity-related GTPase family M protein (IRGM), 297 Immunoblots for LC3 and SQSTM1/p62, 201 Immunoblotting, 284 Immunohistochemistry (IHC), 171, 201 Immunological pathways, 296 In vitro methods, 198–203 autophagy detection kits, 200t chemical inducers and inhibitors of autophagy process, 199t flow cytometry–based methods, 202 immunoblots for LC3 and SQSTM1/p62, 201 LC3 fluorescence microscopy, 201–202 and p62 IHC, 201 nanoparticles, 202 tandem GFP-RFP-LC3 to assess autophagic flux, 202 TEM, 198–200 In vivo methods, 203 Induced autophagy pathway, 226–228 Inevitable death, 8 Infectious diseases, 205–206 Inflammasome, 310 Inflammation, 49 Inhibitor treatment, 284–285 Inhibitors, 94 Innate immunity autophagy machinery and, 305–313

Index

autophagy machinery effects between adaptive and, 310–311 autophagy-related genes in autoimmunity, 311–313 in innate immune mechanisms of pathogen elimination, 307–308 regulation of innate immune signaling pathways, 308–310 selective autophagy, 313–318 innate immune response, 310–311, 314 Inositol requiring 1 (IRE1), 13, 263–264 Inositol-requiring transmembrane kinase/ endonuclease (ITRE1), 27 Insulin-like growth factor (IGF-1), 109, 250 IGF-1-PI3K-Akt pathway, 250 Interaction, Atg9, 185f Interferon regulatory factor 3 (IRF3), 309 Interleukin (IL), 314 IL-1β, 62 Interphotoreceptor matrix (IPM), 107 synthesis, 108 Intestinal autophagy autophagy, 292–293, 294f epithelial autophagy, 298–299 in host defense against Salmonella, 297–299, 299f invasion of Salmonella into intestinal epithelium cells, 295–297, 296f Salmonella, 293–295 Intestinal epithelium cells, Salmonella invasion into, 295–297, 296f Intracellular bacterial infection, autophagy in, 47 homeostasis, 146 proteins, 24 protein degradation, 28 Intraneuronal amyloid beta accumulation, 173–174 Intrinsic apoptosis–autophagy, 275 Intrinsic pathway of apoptosis, 272 Intrinsically disordered regions (IDRs), 25 Ionizing radiation (IR), 215 IPM. See Interphotoreceptor matrix (IPM) IR. See Ionizing radiation (IR) IRE1. See Inositol requiring 1 (IRE1) IRF3. See Interferon regulatory factor 3 (IRF3) IRGM. See Immunity-related GTPase family M protein (IRGM) Iron-binding proteins in RPECs, 113 Isolation membranes, 134, 146, 149–151, 273 Atg5-positive, 151 marker protein, 152 Isoleucine, 224 Isothiocyanates (ITCs), 23 ITCs. See Isothiocyanates (ITCs) ITRE1. See Inositol-requiring transmembrane kinase/ endonuclease (ITRE1)

341

J c-Jun N-terminal kinases (JNK), 113–114

K Kauffman–White classification scheme, 293–295 Kelch-like ECH-associated protein 1 (KEAP1), 240–241 Keratinocytes, 147

L LAMP. See Lysosomal-associated membrane protein (LAMP) LC3-associated phagocytosis (LAP), 47, 307–308, 314–318 LC3-interacting region (LIR), 57, 147–148, 307 LC3. See Light chain 3 (LC3) LDs. See Lipid droplets (LDs) Lectin-binding proteins, 11 Legionella pneumophila, 308 Leucine, 224 zipper, 262 Leupeptin, 94 Lewy bodies, 50 Lewy neuritis, 168–169 Light absorption, 108 light-sensitive pigments, 109 RPECs protection from, 110–111 Light chain 3 (LC3), 16, 33, 196, 274 fluorescence microscopy, 201–202 IHC, 201 immunoblots for, 201 LC3-B protein, 137–138 LC3-II, 111–112, 146, 198, 274 microtubule-associated, 30–31 protein, 166 Lipid droplets (LDs), 122 Lipid homeostasis, 120, 122, 129 Lipid metabolism lipid metabolism-related diseases, 122 proteasome linking, 123–126 REGγ-SirT1 cross talk modulates autophage activity in, 126–129 REGγ-SirT1 regulates, 127–129 Lipidated LC3. See Light chain 3 (LC3)—LC3-II Lipofuscin, 110, 112–113 Lipophagy, 65–67 Lipopolysaccharides (LPS), 293–295 Lipoprotein receptor-related protein-1 (LRP1), 53 LIR. See LC3-interacting region (LIR) Live-cell imaging autophagy regulates protein turnover, 134–135 mitotic autophagy, failsafe mechanism, 135–136 monitoring nonclassical substrate of autophagy, 136–138

342

Index

Long noncoding RNAs (lncRNAs), 253 LPS. See Lipopolysaccharides (LPS) LRP1. See Lipoprotein receptor-related protein-1 (LRP1) Lysine, 224 residues, 160–161 Lysophagy, 67 Lysosomal deacidifying agents, 97 efflux transporter spinster, 18 enzymes, 196 Lysosomal-associated membrane protein (LAMP), 15, 292 LAMP2-A, 224 LAMP-2a ransporter, 15 Lysosomes, 11

M 3-MA. See 3-Methyladenine (3-MA) Machinery flux, 92, 94–96 Macroautophagy. See Autophagy Macrophages, internalized Salmonella in, 295–296 Macular degeneration, autophagy in, 45–46 Major histocompatibility complex (MHC), 310–311 class II genes, 262 Malnutrition, 7 Mammalian cells, 28 autophagosome formation, 15 autophagy in, 10–11 Mammalian intestinal epithelia, 297 Mammalian lethal with Sec13 protein 8 (mLST8), 41 Mammalian target of rapamycin (mTOR), 18, 34–35, 111–112, 237–238, 278, 304 inhibitors, 97 response by, 42 role, 41–42 Mammalian target of rapamycin complex 1 (mTORC1), 151–152, 246–247 Mammals autophagy, regulation in, 221–223 MAVS. See Mitochondrial antiviral signaling (MAVS) MDC. See Monodensylcadaverine (MDC) Mechanistic target of rapamycin. See Mammalian target of rapamycin (mTOR) MEFs. See Mouse embryonic fibroblasts (MEFs); Murine embryonic fi broblasts (MEFs) Melanin granules, 106–107 Melanoma growth stimulatory activity (MGSA), 109 Membrane binding, 16 Rab-type small GTPases in membrane trafficking, 144 remodeling in autophagy, 146 Membranous structures, 146

Metabolic diseases, 206–207 disorders, 120 SirT1 as metabolic sensor, 127 METH. See Methamphetamine (METH) Methamphetamine (METH), 34 Methionine sulfoxide reductases (Msrs), 110–111 Methyl methane sulfonate (MMS), 230 3-Methyladenine (3-MA), 122 Methylglyoxal, 113–114 MGSA. See Melanoma growth stimulatory activity (MGSA) MHC. See Major histocompatibility complex (MHC) Microautophagy, 14, 121, 166, 292 MicroRNAs (miRNAs), 48–49, 248–250 Microscopy-based assays, 201–202 Microtubule-associated LC3, 30–31 Midbody ring (MR), 135 miRNAs. See MicroRNAs (miRNAs) Misfolded proteins, 19, 27 Mitochondria(l), 68 dysfunction, 55 fusion and fission, 56 pathway of apoptosis, 272 Mitochondrial antiviral signaling (MAVS), 309 Mitochondrial DNA (mtDNA), 49, 314 Mitochondrion, 270 Mitophagy, 67–68, 149, 223–224, 313–314. See also Pexophagy receptors, 313 Mitosis, 134–135 Mitotic autophagy, 135–136 mLST8. See Mammalian lethal with Sec13 protein 8 (mLST8) MMS. See Methyl methane sulfonate (MMS) Molecular chaperones, 26 proteins, 21 Molecular level, autophagy in, 304 Molecular mechanisms, 20 Molecular switch, 126–129 REGγ-SirT1 regulates lipid metabolism, 127–129 SirT1 as nutrient/metabolic sensor, 127 Molten globule, 63 Monodensylcadaverine (MDC), 203 Morphological polarity, 106–107 Motion, 23 Mouse embryonic fibroblasts (MEFs), 147, 226 Mouse hepatitis virus, 46 Mouse tumor model, 285 MR. See Midbody ring (MR) Mre11-Rad50-Xrs2 complex (MRX complex), 219 Msrs. See Methionine sulfoxide reductases (Msrs) mtDNA. See Mitochondrial DNA (mtDNA)

Index

mTOR. See Mammalian target of rapamycin (mTOR) mTORC1. See Mammalian target of rapamycin complex 1 (mTORC1) Murine embryonic fi broblasts (MEFs), 122 Mut-PrP expression, 27 Mutant huntingtin, 50 aggregates, 167, 170f Mycobacterium, 307 M. bovis, 307 M. marinum, 205–206 M. tuberculosis, 197, 307 Myocardial stress, 48 Myopathies, 206–207

N N-Acetyl cysteine (NAC), 225 N-CAM. See Neural cell adhesion molecule (N-CAM) N-terminal kinase domain, 247–248 N-terminal LIR, 147–148 NAC. See N-Acetyl cysteine (NAC) NAD+-dependent type III deacetylase, 127 NAF-1. See Nutrient-deprivation autophagy factor-1 (NAF-1) Nanoparticles, 202 NBR1. See Neighbor of BRCA1 (NBR1) NCoR. See Nuclear receptor corepressor (NCoR) NDP52. See Nuclear dot protein 52 (NDP52) Nec-1. See Necrostatin-1 (Nec-1) Necroptosis, 55 Necrostatin-1 (Nec-1), 55 Negative elongation factor (Nef), 46–47 Neighbor of BRCA1 (NBR1), 16, 57–58 NEMO. See NF-κB essential modulator (NEMO) NER. See Nucleotide-excision repair (NER) Nerve growth factor (NGF), 109 Neural cell adhesion molecule (N-CAM), 106–107 Neuritic plaques, 168 Neurodegeneration, 204–205 Neurodegenerative disorders, 163 autophagy in, 49–51 cancer vs., 165–166 Neuronal autophagy, 59–60 Neuropeptide receptor 1 (NPR-1), 298–299 Neuroprotectin 1 (NPD1), 109 Neurotoxic, 175–176 Neurotrophin-3 (NT-3), 109 Neutrophils, 52 NF-κB essential modulator (NEMO), 309 NGF. See Nerve growth factor (NGF) NHEJ. See Nonhomologous end joining (NHEJ) Nitric oxide (NO), 62, 108, 260 NLR pyrin domain-containing 3 (NLRP3), 314 Nod-like receptors (NLRs), 309

343

Nonautophagic functions of autophagy-related proteins, 29–30 Nonhomologous end joining (NHEJ), 218–219 Nonphagocytic enterocytes, internalized Salmonella in, 295–296 NPD1. See Neuroprotectin 1 (NPD1) NPR-1. See Neuropeptide receptor 1 (NPR-1) NRF2. See Nuclear factor (erythroid-derived 2)-like 2 (NRF2) NT-3. See Neurotrophin-3 (NT-3) Nuclear dot protein 52 (NDP52), 307 Nuclear factor (erythroid-derived 2)-like 2 (NRF2), 240–241 Nuclear receptor corepressor (NCoR), 161–162 Nucleic acid sensors, 314 Nucleophagy, 68–69 Nucleoporin 62 (p62), 113–114 IHC, 201 protein, 32 Nucleotide-excision repair (NER), 216–217 Nutrient deficiency, 238 Nutrient sensor, SirT1 as, 127 Nutrient-deprivation autophagy factor-1 (NAF-1), 275

O OATL1, 150–151, 150f Obesity, 122 OFD1. See Oral-facial-digital syndrome 1 (OFD1) Omegasomes, 10 OMM. See Outer mitochondrial membrane (OMM) Oncogene-induced senescence, 39 Optineurin (OPTN), 149, 313–314 Oral-facial-digital syndrome 1 (OFD1), 134–135 Organelles, 135, 144 Organic compounds, 53–54 OSs. See Outer segments (OSs) Outer mitochondrial membrane (OMM), 272 Outer segments (OSs), 106 Ox-LDL. See Oxidized low-density lipoprotein (Ox-LDL) Oxidative damage, 41, 111 Oxidative stress, 34, 240–241 RPECs protection from, 110–111 Oxidized low-density lipoprotein (Ox-LDL), 262

P p38 mitogen-activated protein kinases (p38 MAPK), 113–114 P53-mTOR pathway cell death and cell survival, 280–281 ESC8, C-8 cationic lipid containing estradiol as anticancer agent, 281 small molecular–weight cationic lipids as anticancer agents, 280–281 targeted chemotherapy-breast cancer-mTOR pathway cell death, 280

344

Index

p62. See Nucleoporin 62 (p62) PACRG gene, 32 Pan-specifi c inhibitors, 165 Pancreatic duoductal adenocarcinoma (PDAC), 225 Pancreatic eukaryotic initiation factor 2α kinase (PEK), 13 PARK2. See Parkinson protein 2 (PARK2) Parkinson protein 2 (PARK2), 197 Parkinson’s disease (PD), 40, 49–50, 63–64, 160, 168–169, 314. See also Huntington’s disease (HD) HDAC inhibitors, 174–176 PAS. See Phagophore assembly site (PAS) Pathogens, 316 in animal models, 297 elimination, 307–308 PCNA. See Proliferating cell nuclear antigen (PCNA) PD. See Parkinson’s disease (PD); Platycodin D (PD) PDAC. See Pancreatic duoductal adenocarcinoma (PDAC) pDCs. See Plasmacytoid DCs (pDCs) PE. See Phosphatidylethanolamine (PE) PEDF. See Pigment epithelial-derived factor (PEDF) PEK. See Pancreatic eukaryotic initiation factor 2α kinase (PEK) PERK. See PKR-like ER kinase (PERK) Peroxisome proliferator-activated receptor γ (PPARγ), 127–128 Peroxisomes, 69–70, 224 Pexophagy, 69–72, 224. See also Mitophagy in yeast, 70–72 Phagocytosis, 112 of photoreceptor OS and photoreceptor renewal, 109 Phagophore assembly site (PAS), 70, 182, 187–188, 220–221, 250 reservoirs contribute to formation of, 186–187 Phagophores. See Isolation membranes Phase I clinical trials, 18–19 Phase II clinical trials, 18–19 Phenylalanine, 224 Phosphatidyl inositol 3′ kinase-like kinase (PIKK), 216–217 Phosphatidylethanolamine (PE), 16, 146, 274, 297 Phosphatidylinositol-3-phosphate (PI3P), 188–189, 221–223 Phosphatidylinositol-3-phosphate-positive domains (PtdIns3P-positive domains), 10 Phosphoinositide 3-kinase (PI3K), 7, 19, 35, 111–112, 219, 276–278 PI3K-AKT-mTOR signaling pathway, 276–287, 277f cell death, 278–279 cell death and cell survival, 280–281 cell proliferation/cell cycle, 279–280 Phospholipase D (PLD), 251 Phosphorylated alpha-synuclein, 175

Phosphorylation, 19–20, 171 phosphorylation-dependent regulatory mechanism, 246 Photomultiplier tubes (PMT), 136–137 Photoreceptor OS and renewal, 109 Photoreceptor outer segments (POS), 318 PI3K. See Phosphoinositide 3-kinase (PI3K) PI3P. See Phosphatidylinositol-3-phosphate (PI3P) Piecemeal microautophagy of nucleus (PMN), 61 Pigment epithelial cells αB-crystallin and autophagy, 114–115 AMD, 111 autophagy in RPEs, 111–114 cellular junctions, 108 cytoskeletons, 108 exposure to potential damage, 110 function of RPE, 108–110 functional polarity and heterogeneity, 107 morphology, 106 polarity, 106–107 protection from light and oxidative stress, 110–111 regional heterogeneity, 107 Pigment epithelial-derived factor (PEDF), 107 PIKK. See Phosphatidyl inositol 3′ kinase-like kinase (PIKK) PINK1. See Putative kinase 1 (PINK1) PKR-like ER kinase (PERK), 13 Plasmacytoid DCs (pDCs), 309 Platycodin D (PD), 251 PLD. See Phospholipase D (PLD) Pml. See Promyelocytic leukemia (Pml) PMN. See Piecemeal microautophagy of nucleus (PMN) PMT. See Photomultiplier tubes (PMT) Polarity functional, 107 morphological, 106–107 Polio virus, 46 Polyglutamine tract, 167 POS. See Photoreceptor outer segments (POS) Posttranscriptional modification of ULK1, 248–250 Posttranslation modifications, 74–75 Potent anticancer agent against ER-positive, ESC8, 281–282 PPARγ. See Peroxisome proliferator-activated receptor γ (PPARγ) pRB. See Promoting retinoblastoma protein (pRB) Preautophagosomal structure. See Phagophore assembly site (PAS) Premature senescence, 39 Prion protein (PrP), 12 Proliferating cell nuclear antigen (PCNA), 216–217 Proliferative vitreoretinopathy (PVR), 114 Proline/serine-rich (PS), 247 Promoting retinoblastoma protein (pRB), 217

Index

Promyelocytic leukemia (Pml), 171–173 Proteasomal activators, 123–124 Proteasome inhibitors, 113–114 linking autophage and lipid metabolism, 123–126 REGγ and Ub-independent proteasome systems, 123–124 REGγ regulates hepatic lipid metabolism, 124–125 Proteasome 26S subunit, ATPase 3 (Psmc3), 171 Proteasome 26S subunit, non-ATPase, 171 Proteasome subunit, α type 3 (Psma3), 171 Protein folding, 24 disorders, 167–169 AD, 168 HD, 167–168 PD, 168–169 Protein(s), 20–21, 214–217 aggregation, 28–29, 31 autophagy regulating protein turnover, 134–135 domains, 21 folding, 22f formation of protein structure, 20f kinase complex, 151–152 phosphorylation, 19–20 synthesis, 19–28 abnormal proteins, 24–26 cellular proteins, 21–22 disulfide bonds, 22–23 ER, 26–27 ER and apoptosis, 27 methods, 24 molecular chaperones, 26 molecular mechanisms, 20 unfolded polypeptide, 25f trafficking, 27 Proteomic approach, 149 Proteopathies, 167–169 AD, 168, 173–174 HD, 167–173 HDAC inhibitors in, 169–176 PD, 168–169, 174–176 Proximal tubules, 242 PrP. See Prion protein (PrP) PS. See Proline/serine-rich (PS) PS-1 mutation, 96–97 Psma3. See Proteasome subunit, α type 3 (Psma3) Psmc3. See Proteasome 26S subunit, ATPase 3 (Psmc3) Psmd10, 10 (Psmd10). See Proteasome 26S subunit, non-ATPase PtdIns3P-positive domains. See Phosphatidylinositol-3phosphate-positive domains (PtdIns3P-positive domains) Putative kinase 1 (PINK1), 197 PVR. See Proliferative vitreoretinopathy (PVR)

345

Q Quality control autophagy, 10

R Rab GTPases, 184–185 Rab-GAPs involved in autophagy, 147–152 membrane remodeling in autophagy, 146 Rab-type small GTPases in membrane trafficking, 144, 145f Rab18, 151 Rab3GAP1, 151 Rab3GAP2, 151 Rab7, 149 RAGE. See Receptor for advanced glycation end products (RAGE) RAL. See 11-cis Retinal (RAL) Rapamycin, 285 treatment, 230 Ras homolog enriched in brain (Rheb), 278 RAS-MEK signaling, 97 RavZ bacterial effector, 308 RB. See Retinoblastoma (RB) Reactive nitrogen intermediate (RNI), 296 Reactive oxygen intermediate (ROI), 296 Reactive oxygen species (ROS), 7, 33–34, 223–224, 260, 313 production, 240 Receptor for advanced glycation end products (RAGE), 275 Receptor-interacting protein-1 (RIP1), 55 REG activators, 125 Regional heterogeneity, 107 Regulation, 264 REGγ proteasome, 123 regulates hepatic lipid metabolism, 124–125 REGγ-SirT1 cross talk modulates autophage activity, 126–129 REGγ-SirT1 regulates lipid metabolism by modulating autophagy, 127–129 SirT1 as nutrient/metabolic sensor, 127 systems, 123–124 Repair of DNA damage, 218 Replication factor c subunits (RFC subunits), 216–217 Replication protein A (RPA), 216–217 Replicative senescence, 39 Reporter model system, 203 Reticulophagy, 72–73 Retinal homeostasis, autophagy in, 112 Retinal pathologic conditions and autophagy of RPECs, 113 Retinal pigment epithelial cells (RPECs), 45–46, 106 aging and autophagy in, 112–113 αB-crystallin and autophagy in, 115

346

Index

Retinal pigment epithelial cells (RPECs) (Continued) autophagy in experimental systems, 113–114 involvement in RPECs demise, 114 of iron-binding proteins in RPECs, 113 in RPECs homeostasis, 112 retinal pathologic conditions and autophagy of, 113 Retinal pigment epithelium (RPE), 106, 318 autophagy in, 111–114 function Bruch membrane and IPM synthesis, 108 in immune privilege, 110 light absorption, 108 phagocytosis of photoreceptor OS and photoreceptor renewal, 109 secretion, 109 transepithelial transport of molecules and ions, water, 109 visual cycle, 109 11-cis Retinal (RAL), 318 Retinoblastoma (RB), 280 RFC subunits. See Replication factor c subunits (RFC subunits) Rheb. See Ras homolog enriched in brain (Rheb) RhoA, 135 Ribonucleotide reductase 1 (Rnr-1), 230 Ribophagy, 73–74 Ribosome, 73–74 Rickettsia-like alpha-protobacterium, 37 RIP1. See Receptor-interacting protein-1 (RIP1) RNAse L system, 46 RNAse pathway, 46 RNI. See Reactive nitrogen intermediate (RNI) Rnr-1. See Ribonucleotide reductase 1 (Rnr-1) ROI. See Reactive oxygen intermediate (ROI) ROS. See Reactive oxygen species (ROS) RPA. See Replication protein A (RPA) RPE. See Retinal pigment epithelium (RPE) RPECs. See Retinal pigment epithelial cells (RPECs) Rubicon, 316

S S/MRM. See Selected/multiple reaction monitoring (S/ MRM) Saccharomyces cerevisiae, 34, 182, 247, 292 SAHA. See Suberoylanilide hydroxamic acid (SAHA) Salmonella, 293–295 intestinal autophagy in host defense against, 297– 299, 299f invasion into intestinal epithelium cells, 295–297, 296f S. enterica, 293–295 S. typhimurium, 293–295 Salmonella pathogenicity islands (SPI), 295

Salmonella-containing vacuole (SCV), 295–296 SASP. See Senescence-associated secretory phenotype (SASP) SBI-0206965, FAK inhibitor, 254–255 Scaffold protein Claspin, 217 SCV. See Salmonella-containing vacuole (SCV) Selected/multiple reaction monitoring (S/MRM), 208 Selective autophagy, 56–75, 146, 223, 313–318. See also Autophagy allophagy, 58–59 axonophagy, 59–60 chromatophagy, 60–61 ciliophagy, 61–62 crinophagy, 62 exophagy, 62–64 glycophagy, 64 LAP, 314–318 lipophagy, 65–67 lysophagy, 67 mitophagy, 67–68, 313–314 nucleophagy, 68–69 pexophagy, 69–72 reticulophagy, 72–73 ribophagy, 73–74 xenophagy, 74–75 zymophagy, 75 Self-antigen, 317 Senescence, 39, 43, 228–229 Senescence-associated secretory phenotype (SASP), 228–229 Sequestosome-1 (SQSTM1), 16 SER membranes. See Smooth endoplasmic reticulum membranes (SER membranes) Serine/threonine (SQ/TQ), 216–217 protein kinase expression, transcriptional regulation, and posttranscriptional modification of ULK1, 248–250 structure of ULK1, 247–248 ULK1-mAtg13-FIP200-Atg101 complex, 248 Seven Sirtuins (SIRT-7), 42–43 Shigella flexneri, 205–206 Sigma receptor (SR), 280–281 Signaling pathways, 305–306 Silent information regulator 2 (Sir2), 42–43, 163 Single-strand DNA (ssDNA), 215 Sir2. See Silent information regulator 2 (Sir2) siRNA treatment, 285 SIRT-7. See Seven Sirtuins (SIRT-7) Sirtuin 1 (SirT1), 123, 266 as nutrient/metabolic sensor, 127 Sirtuins, 42–43, 163 Skeletal muscle, aging on, 44 SLE. See Systemic lupus erythematosus (SLE)

Index

Small molecular–weight cationic lipids as anticancer agents, 280–281 Small molecule–mediated simultaneous induction apoptosis, 270–273 autophagy, 273–274 breast cancer, 276 cross talk between apoptosis and autophagy, 274–276 ESC8, 286f ESC8-PI3K-AKT-mTOR pathway, 285 mediates intrinsic apoptotic pathway in breast cancer cell lines, 282–284 potent anticancer agent against ER-positive, 281–282, 282f treatment leads to apoptosis and tumor regression, 285 PI3K-AKT-mTOR signaling pathway, 276–287, 277f Small ubiquitin-like modifiers (SUMO), 167 Smooth endoplasmic reticulum membranes (SER membranes), 64 SMT3 suppressor of mif two 3 homolog 2 (Sumo2), 173 SNARE. See Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) SOD1. See Superoxide dismutase 1 (SOD1) Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE), 187 SPI. See Salmonella pathogenicity islands (SPI) Splicing, 263–264 SQ/TQ. See Serine/threonine (SQ/TQ) SQSTM1. See Sequestosome-1 (SQSTM1) SQSTM1/p62, immunoblots for, 201 SR. See Sigma receptor (SR) ssDNA. See Single-strand DNA (ssDNA) Staining, 282–284 Starch-binding domain-containing protein 1 (Stbd 1), 64 Starvation-induced autophagy, 111–112, 149 Starvation-induced macroautophagy, 220–221 Stbd 1. See Starch-binding domain-containing protein 1 (Stbd 1) Steatosis, 65–66 Stem cells, 43 Steroid hormones, 276 Streptococcus, 307 Stress, 5, 27 ER, 12–13, 251 myocardial, 48 oxidative, 34, 240–241 response, 263–264 Suberoylanilide hydroxamic acid (SAHA), 163 SUMO. See Small ubiquitin-like modifiers (SUMO) Sumo2. See SMT3 suppressor of mif two 3 homolog 2 (Sumo2) Superoxide dismutase 1 (SOD1), 50 Systemic lupus erythematosus (SLE), 207, 309, 312

347

T T-regulatory cells (Tregs), 110 T2D. See Type 2 diabetes (T2D) TAF(II)250. See TATA-binding protein-associated factor (TAF(II)250) Tagged autophagy genes, 203, 203t Tamoxifen, 287 Tandem GFP-RFP-LC3 to assess autophagic flux, 202 TANK-binding kinase 1 (TBK1), 253–254 Target of rapamycin complex 1 (TORC1), 221 Target-of-rapamycin (TOR), 293 Targeted chemotherapy-breast cancer-mTOR pathway cell death, 280 TATA-binding protein-associated factor (TAF(II)250), 161 TBC domain. See Tre-2/Bub2/Cdc16 domain (TBC domain) TBK1. See TANK-binding kinase 1 (TBK1) TECs. See Thymic epithelial cells (TECs) TEM. See Transmission electron microscopy (TEM) Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL), 285 TFEB. See Transcription factor EB (TFEB) TfR. See Transferrin receptor (TfR) TGF-β. See Transforming growth factor-β (TGF-β) TGN. See Trans-Golgi network (TGN) TGs. See Triglycerides (TGs) Therapeutic strategy for targeting ULK1 in cancers, 253–255, 254f Thioredoxins (Trx), 110–111 Thymic epithelial cells (TECs), 311 TIR-domain-containing adaptor protein inducing IFN-β (TRIF), 298 TLRs. See Toll-like receptors (TLRs) TNBC. See Triple-negative breast cancer (TNBC) TNF. See Tumor necrosis factor (TNF) TNF-related apoptosis inducing ligand receptor (TRAIL receptor), 272 Toll-like receptors (TLRs), 38–39, 291–292 TOR. See Target-of-rapamycin (TOR) TORC1. See Target of rapamycin complex 1 (TORC1) Toxoplasma gondii, 308 TRAIL receptor. See TNF-related apoptosis inducing ligand receptor (TRAIL receptor) TRAIL receptor 5 (DR5), 275–276 Trans-Golgi network (TGN), 148–149 Transcription factor EB (TFEB), 196 Transepithelial transport of molecules and ions, water, 109 Transferrin receptor (TfR), 295–296 Transforming growth factor-β (TGF-β), 109–110 Transgenic mouse model, 93–94 Translation, 278–279

348

Index

Transmission electron microscopy (TEM), 198–200 HCT116 cells, 200f Tre-2/Bub2/Cdc16 domain (TBC domain), 144 TBC domain–containing proteins, 144 TBC1D2/Armus, 147 TBC1D5, 147–148 TBC1D14, 148–149 TBC1D15, 149 TBC1D17, 149 TBC1D25, 150–151 Tregs. See T-regulatory cells (Tregs) Trichostatin A (TSA), 163 TRIF. See TIR-domain-containing adaptor protein inducing IFN-β (TRIF) Triglycerides (TGs), 122 Triple-negative breast cancer (TNBC), 276 Trx. See Thioredoxins (Trx) TSA. See Trichostatin A (TSA) Tumor growth ULK1 promoting, 251 ULK1 suppressing, 252–253 Tumor necrosis factor (TNF), 272, 309 TNFα, 55 Tumor regression, ESC8 treatment leads, 285 Tumor-suppressor protein, 197 Tumorigenesis, autophagy in, 35–37 TUNEL. See Terminal deoxynucleotidyl transferasemediated dUTP nick-end labeling (TUNEL) Type 2 diabetes (T2D), 120 Type I interferon (Type I IFN), 308–309

U Ub-independent proteasome systems, 123–124 UBA. See Adaptor proteins through ubiquitin-binding protein (UBA) UBA domain. See Ubiquitin-associated domain (UBA domain) Uba7. See Ubiquitin-like modifier activating enzyme 7 (Uba7) Ube2e3. See Ubiquitin-conjugating enzyme E2E 3 (Ube2e3) Ube2k. See Ubiquitin-conjugating enzyme E2K (Ube2k) Ubiquitin, 166 proteasome, 32 ubiquitin-binding proteins, 28–29 Ubqln2, 171–173 Ubiquitin-associated domain (UBA domain), 70 Ubiquitin-conjugating enzyme E2E 3 (Ube2e3), 171–173 Ubiquitin-conjugating enzyme E2K (Ube2k), 171–173 Ubiquitin-like modifier activating enzyme 7 (Uba7), 173 Ubiquitin-like proteins (UBL proteins), 29–30 conjugation systems, 246–247, 274 proteins, 30

Ubiquitin-proteasome system (UPS), 23, 134, 166, 220 degradation pathway, 21 Ubiquitin-receptors, 75 Ubiquitin-specific peptidase 28 (Usp28), 171–173 Ubiquitin-specific protease 29 (Ups29), 171 Ubiquitin-specific protease 3 (Ubp3), 74 Ubiquitination, 47, 55, 74–75 ubiquitination-related gene altered expression, 171–173, 172t UBL proteins. See Ubiquitin-like proteins (UBL proteins) Ubp3. See Ubiquitin-specific protease 3 (Ubp3) ULK1-mAtg13-FIP200-Atg101 complex, 248 ULK1. See Unc51-like protein kinase 1 (ULK1) Ultraendurance exercise, 7 Ultraviolet radiation (UV radiation), 215 Unc-51. See Uncoordinated-51 (Unc-51) Unc51-like protein kinase 1 (ULK1), 196, 246 in cancers, therapeutic strategy for targeting, 253– 255, 254f expression in cancers, 250–251 preinitiation complex, 246–247 promoting tumor growth, 251 regulation network, 252f serine/threonine protein kinase, 247–250 suppressing tumor growth, 252–253 Unconventional secretion method, 62 Uncoordinated-51 (Unc-51), 246 Unfolded protein response (UPR), 12–13, 73 UPS. See Ubiquitin-proteasome system (UPS) Ups29. See Ubiquitin-specific protease 29 (Ups29) Usp28. See Ubiquitin-specific peptidase 28 (Usp28) UV radiation. See Ultraviolet radiation (UV radiation) UV radiation-resistant associated proteins (UVRAG proteins), 221–223, 304–305 UVRAG proteins. See UV radiation-resistant associated proteins (UVRAG proteins)

V Vacuolar protein sorting protein 34 (Vps34), 135, 221–223 Vacuolar proton-pump ATPase (V-ATPase), 295–296 Valine, 224 Vascular endothelial growth factor (VEGF), 107 Vascular smooth muscle cell (VSMC), 260 Vertebrate genomes, 246–247 Vesicle, 144 Vinblastine, 94 Viral defense and replication, autophagy in, 46–47 Visual cycle, 109 performance, 112 Vitamins, 7–8 vitamin A, 109 vitamin C, 109

Index

W Warburg effect, 238 Warburg Micro syndrome, 151 Water molecules, 23 Western blot analysis, 93–94 White adipose tissue (WAT), 122

X X-Box Binding Protein 1 (XBP1), 262–264 cell-type dependent, 266 in ECs, atherosclerosis, and autophagy, 264 mRNA splicing, 264–266, 265f Xenophagy, 37, 74–75, 196, 297, 307

Y Yeast autophagy regulation in, 221–223 pexophagy in, 70–72

Yeast autophagy Atg9 roles in autophagy, 183–184 at preautophagosomal structure, 187–188 recycling, 188–189 trafficking via ER and Golgi compartments, 184–186, 185f vesicles, 186–187 reservoirs contribute, 186–187

Z Zymophagy, 75

349